The Clinical Intelligence Your Population Needs Is Already in the Record.
Care gaps. Risk scores. Quality measures. HCC opportunities. The data that drives population health strategy is trapped in unstructured clinical notes. Hindsait's CNLP API extracts it, at panel scale, in real time.
What Hindsait Powers
From individual records to population-level intelligence.
HEDIS / Stars / NCQA Quality Reporting
CNLP API extracts quality measure data elements from clinical notes automatically, identifying documented care gaps, preventive services, and clinical outcomes that don't appear in claims data. Population-level quality reporting .
HCC Coding Gap Identification
Processes member records to identify suspect HCC conditions that are documented in clinical notes but not yet captured in coded diagnoses, closing RAF gaps before the measurement period ends.
Risk Stratification
ML models built on clinical indicators extracted by CNLP identify high-cost, high-risk patients for proactive outreach, before they generate avoidable acute events. Works across Medicare Advantage, MSSP, and commercial risk arrangements.
Disease Registry Automation
Automatically populate chronic disease registries, diabetes, COPD, CHF, CKD, from clinical notes without manual entry. NSQIP and surgical outcome data extraction supported for hospital quality programs.
Care Gap Detection
Identifies care gaps documented in records but not captured in claims, preventive screenings, medication adherence, follow-up visits. Drives targeted outreach before the quality measure period closes.
ACO & Value-Based Care Analytics
Supports MSSP, Medicare Advantage risk arrangements, and PCMH programs by processing complete patient panel records, surfacing quality measure performance, cost risk, and RAF optimization opportunities at panel scale.
Unlock the clinical intelligence already inside your records.
100M+ records processed. 6 to 8 week deployment. CNLP API built specifically for healthcare-specific clinical language.
This Is What Healthcare AI Should Look Like.
Production-deployed with WPS Health. Audit-ready by design. Proven to reduce prior authorization review time by 53%. Hindsait turns clinical records into decision-ready intelligence for prior authorization, clinical review, and payment integrity.
Gartner® recognized, built on 12 years of healthcare-specific clinical NLP, and shaped by 100M+ medical records processed across real clinical workflows.
53%Prior Auth (PA) EfficiencyDocumented across real PA deployments
100M+Medical Records ProcessedSince 2013, across real clinical workflows
12 yrsHealthcare-Specific AI R&DCNLP trained on clinical data since 2013
3×Faster PA DecisionsTurnaround time across deployed health plans
6–8 wksWeeks to Live DeploymentBuilt to complement, not replace existing systems
PALIVE
Live in ProductionProduction-deployed prior authorization (PA) workflows with audit-ready clinical oversight
HITRUST CSFCertified InfrastructureHIPAA + SOC 2 · Enterprise-grade PHI protection at every layer
WPS Health SolutionsLive Production ClientMedicare Administrative Contractor · Jurisdictions 5 & 8
Florida BlueStrategic InvestorGuideWell · One of the largest Blues Plans in the country
Why Hindsait Is Different
Clinical AI that has earned its place in production.
Production deployment in prior authorization requires evidence, controls, and auditability—not marketing claims. Automated evidence matching for clinically clear cases.
With Florida Blue among our strategic backers and twelve years of healthcare-specific CNLP training, Hindsait brings accumulated clinical intelligence built through years of real clinical data, deployment, and refinement.
01
Proven at production scale
100M+ records processed. Live in production at WPS Health, a Medicare Administrative Contractor, processing real PA workflows. Already operating in live authorization workflows.
02
Human-in-the-loop where it matters
Automated evidence matching for clinically clear cases. Clinician review for complex determinations. Live in 6–8 weeks, built to complement, not replace your existing UM, PA, EHR, or claims systems.
03
53% PA efficiency. Verified.
A documented outcome across real deployments, not a modeled projection. Measured across prior authorization and clinical audit workflows, the Hindsait platform delivered 30% time savings.
04
Flexible Deployment. Your Environment, Your Terms.
Deploy on-premises or on cloud — GCP, AWS, or Azure — based on your data governance and security requirements. Same platform, same clinical intelligence, same audit trail. No vendor lock-in. No forced migration.
Production Deployment · Prior Authorization
53%
Efficiency improvement across prior authorization and clinical review workflows
Live in production at WPS Health, a Medicare Administrative Contractor for Jurisdictions 5 & 8. Automated evidence matching where clinical criteria are conclusively met. Clinicians in the loop for complex determinations.
"
Having the Hindsait team deeply integrated with our operational SME's, we were not only able to cut our medical review time by over 50%, we also developed new and novel additional uses and custom capabilities with the Hindsait platform to add greater value to our organization, staff, and customers.
BJ
Brian Janssen
Chief Information Officer, WPS Health Solutions
How Hindsait Works
Clinical intelligence, built in layers.
Every Hindsait decision starts with the same foundation, structured clinical intelligence extracted from the documents you already have. One base layer. Every use case above it.
Use Case Layer, Powered by IDP Clinical Intelligence
Prior Authorization
PA decision support. Criteria-matched. Audit-ready. Human-in-the-loop for complex cases.
Production Deployed3× Faster
UM & Clinical Review
MCG, InterQual, LCD/NCD criteria applied consistently across every concurrent and retrospective review.
Guideline-Aligned30% Time Savings
Payment Integrity
Claims anomaly detection, post-payment clinical review, FWA pattern analysis across your full population.
FWA DetectionPopulation Scale
Risk Adjustment & HCC
HCC coding gap identification, RAF score optimization, and RADV-ready audit trail for ACOs and health plans.
RAF OptimizedRADV-Ready
Revenue Cycle & Coding
Automated ICD-10 to HCC crosswalk, AI-assisted coding with human review, and provider prior authorization.
Structured clinical intelligence feeds every use case above
Foundation Layer
Hindsait IDP
Intelligent Document Processor
One foundation layer, every use case above it. IntelliSync, our automated policy intellgence layer, continuously monitors CMS, payor policies, and clinical guidelines, so every decision the pipeline produces is always aligned to current criteria, without manual updates.
Ingest
Any source any format
Clinical NLP
Context-aware understanding
Extract & Summarize
Key facts GenAI summary
Score & Route
Evidence strength smart routing
Deliver
Real-time API audit trail
95%
Extraction Accuracy
<30s
Per Document
50+
Clinical Entity Types
Who We Serve
Built for every side of the clinical decision
One platform. Three distinct solution sets, each designed for the workflows, pain points, and buyers that define that segment of healthcare.
Payor Solutions
Health Plans & Payors
Automate PA, UM, clinical audit, and payment integrity while meeting CMS-0057-F mandates and HEDIS benchmarks, without adding headcount.
CMS-0057-F compliant PA automation
MCG, InterQual, LCD/NCD decision trees
Payment integrity & FWA detection
HEDIS & Stars gap analytics
Explore Payor Solutions →
Pharma Solutions
Pharma & Life Sciences
Accelerate specialty drug access, decode payor policies , and extract real-world clinical evidence to power market access strategy.
Specialty drug PA automation
payor policy monitoring, 100s of plans
Real-world evidence extraction
HEOR & outcomes analytics
Explore Pharma Solutions →
Provider Solutions
Providers & Health Systems
Reduce claim denials, cut documentation burden by 40%, and optimize ACO and value-based care performance from one clinical intelligence layer.
AI documentation, 40% burden reduction
Denial risk scoring pre-submission
MIPS, Stars, HEDIS gap analytics
Predictive readmission alerts
Explore Provider Solutions →
Results & Recognition
Trusted by healthcare's most demanding organizations
Hindsait's technology and creative approach have opened new doors in how we use data to manage our business.
Tina Blasi
CEO, NIA / Magellan
"
Hindsait’s proven AI technology and differentiated platform, coupled with its seasoned executive team, set it apart.
Ateet Adhikari
Vice President, Healthbox
"
We worked with Hindsait to fine-tune predictive analytics that would enhance our efficiency without compromising quality.
Laurel Douty
COO, Magellan Healthcare
"
Hindsait's ability to identify meaningful clinical insights creates a better pathway for care delivery across our entire network.
Renee Finley
Head of Innovation, GuideWell
"
Having the Hindsait team deeply integrated with our operational SME's, we were not only able to cut our medical review time by over 50%, we also developed new and novel additional uses and custom capabilities with the Hindsait platform to add greater value to our organization, staff, and customers.
Every metric to the right comes from a real Hindsait client deployment, not modeled projections. Healthcare Decision Intelligence delivers measurable ROI within the first quarter of deployment.
Built for the buyer who counts cost per review. Hindsait clients report measurable FTE reallocation, faster turnaround, and reduced rework, translating directly to lower administrative cost per clinical decision.
Clinical intelligence that earns its place in production.
From contract to deployment in 6 to 8 weeks. Your records, your use cases, your workflows. We connect to your existing systems. No infrastructure replacement required.
Live in Production · Prior Authorization · Payor Solutions
Clinical Intelligence Built for Health Plans at Production Scale.
53% efficiency improvement. Human-in-the-loop with AI assistance for complex cases.
Hindsait is live in production processing prior authorization requests at WPS Health, the Medicare Administrative Contractor for Jurisdictions 5 & 8. For every case where clinical evidence is clear, Hindsait decides. For complex determinations, your clinicians decide with full AI-surfaced context.
Built specifically for health plans, Blues Plans, TPAs, benefit managers, and self-insured employers.
WPSDEPLOYED
Prior AuthorizationHindsait is live in production at WPS Health, one of the largest Medicare Administrative Contractors in the country
53%
Efficiency ImprovementDocumented across payor & provider workflows using the Hindsait platform
3×
Faster PA DecisionsMeeting 72-hour CMS mandates with capacity to spare
CMS-0057-F requires accelerated turnaround, real time PA capability, and full audit transparency, on legacy systems not built for it.
Hindsait Solution
CMS-aligned PA workflows with full audit trails, 72-hour standard and expedited decision support, compliant out of the box.
Challenge
Manual UM reviews are slow, inconsistent across reviewers and shifts, and costly per case, yet volume only grows.
Hindsait Solution
MCG, InterQual, CMS LCD/NCD guidelines auto-converted into decision-tree worksheets. ADLs, prior therapies, condition progression auto-matched to criteria.
Challenge
Rising fraud, waste, and abuse exposure with limited real time detection capability, most FWA identified only post-payment.
Hindsait Solution
Claims anomaly detection and clinical pattern analytics flag FWA risks before payment, pre-pay intervention reducing recovery burden.
Challenge
HEDIS, Stars, and CMS quality benchmarks increasingly tied to plan revenue, but gap closure requires member-level visibility most plans lack.
Hindsait Solution
Proactive quality gap analytics with actionable member-level care recommendations, closing gaps before benchmark deadlines, not after.
Challenge
TPAs and self-insured employers lack visibility into utilization trends and plan performance across benefit lines.
Hindsait Solution
Unified analytics dashboards providing utilization, cost, and quality KPIs across benefit lines, giving plan managers the performance visibility to act.
Challenge
ACO and value-based contracts require accurate risk scoring to protect shared savings, manual RAF optimization can't keep pace.
Hindsait Solution
Risk stratification engine combining claims, clinical, and SDOH data for accurate RAF and VBC performance, protecting shared savings.
Four Solution Domains
AI across every payor-critical workflow
01
Utilization Management
Medical Necessity Review Automation
Guidelines auto-converted into structured decision-tree worksheets. ADLs, pain assessments, prior therapies, and condition progression auto-matched to criteria, consistent across every reviewer.
MCG, InterQual, CMS LCD/NCD auto-converted to decision trees
Plan-specific criteria and policy integration
One-keystroke SSU audit navigation
Consistent determinations across all reviewers and shifts
02
Prior Authorization
AI-Assisted Prior Auth Decision Support
CMS-compliant 72-hour standard and expedited review workflows. payor-specific criteria matching with documentation scoring. PA volume trend analytics and benchmarking.
CMS-0057-F compliant PA workflows with full audit trail
72-hour and expedited review automation
SSU audit support with one-keystroke record navigation
PA volume trend analytics and benchmarking
03
Clinical & Fraud Analytics
Payment Integrity & FWA Detection
Payment integrity and claims anomaly detection that identifies fraud, waste, and abuse before payment. Clinical pattern analytics across provider networks.
Claims anomaly detection pre- and post-payment
Clinical pattern analytics for FWA identification
Provider network outlier and pattern analysis
HEDIS gap reporting and quality measure analytics
04
Member & Risk Management
Risk Stratification & Population Health
Predictive risk stratification for care management. SDOH-aware chronic disease intervention targeting. ACO and value-based contract performance analytics.
Predictive risk stratification, claims, clinical, and SDOH data
SDOH-aware chronic disease management targeting
ACO and VBC contract performance analytics
Proactive HEDIS and Stars gap closure analytics
How Hindsait Works
From clinical guideline to defensible determination
A four-stage workflow that converts clinical guidelines into consistent, auditable, and CMS-compliant determinations, at any volume, with any payor's specific criteria.
Step 01
Ingest Clinical Guidelines
Hindsait ingests MCG, InterQual, CMS LCDs/NCDs, or plan-specific policies as the authoritative source for review criteria, keeping your AI aligned to the exact standards your plans operate under.
MCG · InterQual · CMS LCD/NCD · Plan-Specific
Step 02
Auto-Convert into Decision-Tree Worksheets
Guidelines are automatically converted into structured decision-tree worksheets, questions, branching logic, and criteria derived directly from the guideline content. No manual authoring. No version drift.
Automated Conversion · No Manual Authoring · Always Current
Step 03
Apply Decision Tree to Medical Records
The decision tree is applied to each medical record under review. ADLs, pain assessments, prior therapies, and longitudinal condition progression are extracted and mapped to criteria automatically.
Reviewers work from pre-populated, policy-aligned worksheets for consistent, defensible determinations. The Hindsait Audit Platform brings users directly to the most relevant record information with a single keystroke, accelerating SSU audits, appeals, and CMS compliance reviews.
One-Keystroke Navigation · Pre-Populated Worksheets · Full Audit Trail
Measurable Business Impact
The outcomes health plans and payors measure
↓UM Review CostAutomated medical necessity review shifts reviewer time from document search to clinical judgment
3×Auth TurnaroundFaster prior auth decisions, meeting 72-hour CMS mandates with capacity to spare
↑ StarsHEDIS & Stars PerformanceProactive member-level gap closure improves plan ratings, protecting Stars revenue bonuses
Select the resource that fits your needs - both are available immediately on form submission.
The full Hindsait payor Solution Brief, capability breakdown, client outcomes, and the WPS Health Solutions case study showing a 30% efficiency gain in medical review processing.
Payor Solution Brief
Complete the form to unlock the full PDF
Download the Payor Solution Brief
Detailed capabilities, client outcomes, and the WPS Health Solutions case study. Your download starts immediately on submission.
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The full WPS Health Solutions white paper on responsible AI deployment in prior authorization - proven outcomes, governance framework, and CMS-aligned automation strategy.
Responsible AI in Prior Authorization
Complete the form to unlock the full white paper
Download the White Paper
Responsible AI governance, CMS-aligned automation strategy, and documented 53% efficiency outcomes from WPS Health Solutions. Download begins immediately on submission.
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Ready to see Hindsait in your UM workflow?
Most health plan clients are in production within 6 to 8 weeks. See a live demo with your own clinical guidelines and document types.
Provider Solutions
Clinical AI That Pays for Itself in Weeks, Not Years.
Hindsait handles the document work so your clinicians can focus on clinical decisions.
Rising claim denials, physician burnout from documentation overload, tightening CMS quality benchmarks, and the shift to value-based reimbursement are compressing performance across health systems.
Hindsait connects clinical, operational, and financial intelligence, so providers spend less time on administrative burden and more time on decisions that matter.
40%
Reduction in documentation burdenAI-assisted case summaries reduce note overhead, giving physicians time back
↓15–20%
Claim denials trending up industrywideDenial management and IntelliSync policy monitoring. Denial risk scoring and documentation gap alerts stop denials before submission
+24%
First-pass PA approval rate liftpayor-specific criteria matching ensures submissions arrive complete the first time
FHIR
Native data lakehouseClinical, claims, and SDOH data unified, no fragmented EHR silos
Provider Pain Points, Addressed Directly
The pressures your organization faces every day
Challenge
Physician burnout from EHR documentation overload, hours of note-writing per shift consuming time that should be spent on patient care.
Hindsait Solution
AI-assisted documentation and automated case summaries reduce note burden by up to 40%, clinical intelligence that writes the administrative record so physicians don't have to.
Challenge
Claim denials increasing 15–20% year-over-year amid payor policy changes, insufficient time to identify documentation gaps before submission.
Hindsait Solution
Denial risk scoring and documentation gap alerts run before claim submission, flagging missing criteria and weak documentation before the claim reaches the payor.
Challenge
Prior authorization delays disrupting patient throughput and care delivery, consuming clinical staff time on manual submissions.
Hindsait Solution
AI-driven prior auth decision support with payor-specific criteria matching, submissions arrive aligned to each payor's exact requirements, first time.
Challenge
Fragmented data across EHRs limiting care coordination and population health visibility, no single view of patient risk across the system.
Hindsait Solution
FHIR-native data lakehouse unifying clinical, claims, and social determinants data, giving care teams and administrators a complete population view in one place.
Challenge
High readmission rates penalizing reimbursement, without the predictive tools to identify at-risk patients before discharge.
Hindsait Solution
Predictive readmission models with proactive care team alerts, identifying patients at risk before discharge so interventions happen at the right moment.
Challenge
ACO shared savings at risk from inaccurate member risk scores and coding errors driving revenue leakage across the system.
Hindsait Solution
ACO risk scoring combining claims, clinical, and SDOH data for accurate RAF optimization. Human-assisted coding with AI accuracy review and full audit trails.
Three Solution Domains
Integrated AI across clinical operations, revenue cycle & population health
01
Clinical Operations
Documentation & Care Intelligence
AI-assisted clinical documentation reduces physician note burden. Care gap alerts, readmission risk scoring, and workflow intelligence support better care coordination decisions.
Care gap and readmission risk alerts for care teams
Workflow intelligence and care coordination support
02
Revenue Cycle
Denial Prevention & Revenue Intelligence
Denial risk scoring and documentation gap detection before submission. Human-assisted coding with AI accuracy review. Prior auth support with payor-specific criteria matching.
Denial risk scoring before claim submission
Documentation gap detection and remediation alerts
Prior auth AI with payor-specific criteria matching
Human-assisted coding with AI accuracy review and audit trail
Revenue leakage identification across service lines
03
Population Health
Risk Stratification & Value-Based Care
SDOH-aware chronic disease management targeting. Quality and regulatory performance analytics for MIPS, Stars, and HEDIS. ACO and MSSP value-based care support with real time population health dashboards.
AI-driven risk stratification with SDOH data integration
MIPS, Stars, and HEDIS gap analytics with care recommendations
ACO, MSSP, and VBC performance dashboards
Predictive readmission models with care team alerts
04
Provider Confidence Scoring
PA Intelligence & Approval Optimization
Score incoming PA requests by clinical evidence strength, provider history, and guideline alignment, helping UM teams prioritize complex cases for physician review, with fairness auditing built in.
Evidence-strength scoring for PA requests
Provider history and guideline alignment scoring
Fairness-audited ML scoring model
Appeals and denial management support
Measurable Business Impact
Outcomes that move the right metrics
↓Claim Denial RateDocumentation gap prevention and denial risk scoring before submission, stopping denials before they happen
40%Clinical EfficiencyReduced documentation burden, faster case summaries, and better care coordination decisions for clinical teams
↑Quality ScoresProactive gap closure for MIPS, Stars, and HEDIS measures, driven by actionable member-level care recommendations
↑VBC PerformanceRisk-adjusted population analytics for ACO and MSSP success, protecting shared savings with accurate RAF optimization
Solution Brief
Download the Provider Solution Brief
Detailed capabilities across clinical operations, revenue cycle, and population health, plus measured outcomes from real provider deployments.
Provider Solution Brief
Complete the form to unlock the full PDF
Download the Provider Solution Brief
Clinical operations, revenue cycle, and population health, all in one document. Download begins immediately on submission.
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Ready to reduce denials and give your physicians time back?
See how Hindsait connects clinical, revenue cycle, and population health intelligence for provider organizations like yours.
Pharma & Life Sciences Solutions
Pharma Pays $20M+ Per Drug for RWE. Hindsait Replaces That.
Hindsait handles the document work so your clinicians can focus on clinical decisions.
Specialty therapies face a gauntlet of payor requirements, step therapy criteria, and coverage policies varying across hundreds of health plans. Most market access teams navigate this manually, without AI to decode payor policies or extract the real-world clinical evidence that changes coverage decisions.
Hindsait's Evidence-Based AI reads the documents your teams can't, at the scale your strategy demands.
Faster
Specialty drug patient accessAI-driven PA automation and step therapy navigation reduce access delays for patients
100s
payor policies monitored continuouslyLCD/NCD changes, formulary updates, and PA criteria shifts, tracked in real time
RWE
CNLP API + IDP, real-world evidence unlockedUnstructured records transformed into HEOR evidence, label expansion support, and VBC data
96%
Clinical extraction accuracyEvidence-Based AI reading physician notes, clinical narratives, and outcomes data
The Market Access Challenge
The clinical evidence for your drug exists. It's just unreadable.
Most of the evidence that would support payor coverage decisions, PA approvals, and market access outcomes lives in unstructured physician notes, faxed treatment histories, and narrative records that no legacy system can process . Hindsait reads them.
Four Market Access Domains
Evidence-Based AI across the full access lifecycle
01
Drug Access
Specialty Drug PA Automation
AI that understands formulary criteria, step therapy requirements, and payor-specific medical necessity standards, accelerating patient access by automating documentation and criteria-matching.
Formulary criteria and step therapy AI navigation
PA documentation generation aligned to payor requirements
payor-specific medical necessity criteria matching
Exception and appeal documentation support
02
Market Access Intelligence
Payor Policy Intelligence at Scale
Monitor and decode payor coverage policies across hundreds of health plans in real time, tracking LCD/NCD changes, formulary updates, step therapy criteria shifts, and PA requirement changes.
Continuous monitoring of payor coverage policies
LCD/NCD coverage decision tracking and analysis
Formulary positioning and tier change alerts
PA requirement change detection and impact analysis
03
Real-World Evidence
Clinical Evidence Extraction for HEOR
Unlock clinical evidence trapped in unstructured medical records, physician notes, treatment narratives, and outcomes documentation, to support HEOR, label expansions, and VBC contracting.
NLP extraction of outcomes from clinical narratives
Treatment pattern and adherence analysis across your full population
Comparative effectiveness evidence from real-world records
Label expansion evidence generation
04
Value-Based Contracting
Outcomes & Risk Adjustment Analytics
AI-powered outcomes tracking and risk score optimization for value-based contracts, connecting drug utilization to clinical endpoints across payor datasets.
Drug utilization to clinical outcomes linkage analytics
Risk adjustment and RAF optimization for VBC contracts
Outcomes tracking across payor member populations
VBC contract performance monitoring and reporting
How It Works
From access barrier to approved therapy
Hindsait's specialty drug access workflow combines payor policy intelligence, clinical documentation AI, and evidence extraction, reducing the administrative burden on prescribers and market access teams at every step.
1
Decode payor Requirements
payor policy intelligence identifies formulary criteria, step therapy requirements, and PA triggers specific to each health plan before submission.
2
Extract Clinical Evidence from Records
Clinical NLP reads the patient record, extracting step therapy history, prior treatment failures, diagnoses, and clinical indicators that support medical necessity.
3
Generate payor-Aligned Documentation
AI generates payor-specific PA documentation with clinical evidence mapped to each payor's criteria, first-time submission accuracy, not iterative rework.
4
Monitor, Appeal & Capture Outcomes
Denial pattern monitoring, exception and appeal support, and outcomes tracking feed continuous improvement of market access strategy.
Market Access Outcomes
PA first-pass approval improvementSignificant
payor policies monitored simultaneously100s
Clinical entity types extracted per record50+
Extraction accuracy, clinical narratives96%
Time from ingestion to structured output<30s
Security certificationSOC 2 + HITRUST
Solution Brief
Download the Pharma & Life Sciences Solution Brief
Specialty drug PA automation, payor policy intelligence, real-world evidence extraction, and VBC analytics, with implementation approach and market access outcomes.
Pharma & Life Sciences Solution Brief
Complete the form to unlock the full PDF
Download the Pharma Solution Brief
Specialty drug PA automation, payor policy intelligence, and real-world evidence extraction in one document. Download begins immediately on submission.
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Ready to accelerate access and unlock your real-world evidence?
See how Hindsait's Evidence-Based AI transforms market access strategy for specialty therapies, from PA automation to payor contracting support.
Payment Integrity & Risk Adjustment
Stop Paying for Claims the Clinical Record Doesn't Support.
Hindsait handles the document work so your clinicians can focus on clinical decisions.
Healthcare loses an estimated $300 billion annually to improper payments, coding errors, and fraud. Most goes undetected, because the clinical evidence needed to identify it is buried in unstructured records that legacy systems cannot read.
Hindsait's Evidence-Based AI reads every clinical document, cross-references every claim, and surfaces the discrepancies that manual review consistently misses, across your full population, without adding headcount.
$300B
Annual improper payment exposureEstimated US healthcare losses to billing errors, fraud, and coding inaccuracies
96%
Clinical extraction accuracySo evidence-based coding validation across millions of records
30%
Time savingsEvidence-Based AI applied to utilization and payment review, documented client outcome
Four Solution Areas
Complete Payment Integrity , across the full revenue cycle
01
Risk Adjustment
Risk Adjustment Intelligence
Validate HCC coding accuracy against actual clinical documentation across your full population. Identify undercoded and overcoded diagnoses, close documentation gaps, and ensure risk scores reflect clinical reality.
96%Coding Accuracy
30%Time Savings
02
Post-Payment Audit
Post-Payment Audit & Recovery
Scale post-payment clinical review without scaling headcount. Hindsait reads clinical records against paid claims, identifies unsupported services, and surfaces overpayment findings, structured, documented, and ready for recovery action.
MillionsRecords / Day
AutoFinding Documentation
03
Fraud Detection
Fraud, Waste & Abuse Detection
Cross-reference claims against clinical records to detect upcoding, unbundling, medically implausible procedures, and provider pattern anomalies that claims-only systems cannot identify.
PatternNetwork Analysis
Real-TimeAnomaly Flagging
04
Payment Integrity
Prospective Payment Integrity
Stop improper payments before they happen. Pre-payment clinical review flags claims with medical necessity concerns or documentation gaps before adjudication, reducing recovery burden and administrative cost.
Pre-PayIntervention
LowerRecovery Cost
Core Capabilities
What Hindsait Payment Integrity actually does
Clinical-to-Claims Cross-Reference
Every claim validated against the underlying clinical record automatically, medical necessity, coding accuracy, and clinical plausibility verified across your full population.
HCC Coding Validation & Capture
CNLP-powered HCC identification across clinical documentation, surfacing both overcoded diagnoses that create liability and undercoded conditions that represent legitimate revenue risk.
Provider Pattern & Network Analysis
Statistical and clinical analysis of provider billing patterns, identifying outliers, specialty anomalies, and coordinated fraud patterns invisible to individual claim review.
Real-Time & Retrospective Review
Pre-payment flags during adjudication for prospective integrity, plus retrospective audit of historical claims populations, covering both prevention and recovery.
Audit Finding Documentation
Every finding structured, evidenced, and documented for recovery action, with supporting clinical citations, coding rationale, and audit trail that satisfies regulatory and legal review standards.
Regulatory & CMS Compliance
RADV audit preparation and defense. CMS risk adjustment data validation alignment. SOC 2 + HITRUST certified infrastructure for sensitive financial and clinical data.
Case Study
See Hindsait Payment Integrity in action , real results
Download the full case study to see how a health plan applied Hindsait's Evidence-Based AI to payment integrity and risk adjustment, including audit methodology, implementation approach, and measured financial outcomes.
Payment Integrity Case Study
Complete the form to unlock the full PDF
Download the Payment Integrity Case Study
Full methodology, implementation approach, and measured financial outcomes from a real Hindsait Payment Integrity deployment. Download begins immediately on submission.
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Ready to recover what's yours and protect what's at risk?
Most clients identify material findings within the first 30 days. See Hindsait Payment Integrity live with your claims population.
Live in Production
Clinical AI · SOC 2 + HITRUST Audited
Smarter, Configurable
Document Intelligence Built for Healthcare.
Master the clinical data you already have.
Your organization is drowning in clinical documents it already owns, medical records, lab reports, clinical notes, guidelines, and policies. Massive volumes. Complex narrative content. Manual review that is slow, error-prone, and inconsistent.
Hindsait IDP automates the entire document intelligence workflow, extraction, summarization, comparison, and highlight, so your teams make faster, more defensible decisions in minutes, not days.
You're drowning in clinical documents you already own.
Healthcare organizations handle massive volumes of unstructured documents every day, medical records, clinical notes, lab reports, guidelines, policies, and large multi-page files with complex narrative content. The volume is growing. The staff is not.
Massive unstructured volume
Medical records, clinical notes, lab reports, and regulatory documents. Most of it narrative, none of it machine-readable.
Time-consuming manual review
Clinicians spend hours searching and comparing documents to extract information needed for a single decision.
Compliance and accuracy risk
Manual extraction is error-prone across reviewers and shifts, creating audit exposure, appeals risk, and quality gaps.
Slowed decision-making
Document backlogs create bottlenecks across PA, UM, audit, and clinical review, increasing costs and limiting efficiency.
SLOW
Manual review of a single complex record takes hours. At volume, it's weeks of reviewer time that should be spent on decisions, not document search.
Hours → Seconds with IDP
COSTLY
Clinical FTE time spent on document review is the most expensive way to extract information that AI can surface automatically at a fraction of the cost.
53% cost reduction in manual effort
INCONSISTENT
What a reviewer extracts on Monday differs from what they extract on Friday after 200 records. AI applies the same rigor to record one million as to record one.
95% accuracy · Every record · Every time
Manual processing puts organizations at high risk of errors, delays, compliance penalties, and adverse audit findings. The longer the backlog, the greater the exposure.
The Solution
Hindsait IDP doesn't just read documents, it understands them.
End-to-end document intelligence workflow, configurable by your team, powered by clinical AI, integrated into your existing systems.
01
Ingest
Any document source or format
→
02
OCR + Vision
Medical-grade recognition
→
03
Clinical NLP
Context-aware extraction
→
04
Extract & Summarize
GenAI-powered summaries
→
05
Deliver & Integrate
Real-time API outputs
Universal Document Ingestion
Hindsait IDP connects to your document sources via secure SFTP, direct API, HL7 FHIR, or the IDP portal. Faxed charts, scanned records, EMR exports, multi-page PDFs, and structured data, all formats accepted, zero re-engineering required.
HL7 FHIR, SFTP, Direct API, Fax Integration
Any file format, PDF, TIFF, DOCX, HL7, CCDA
Single records or batch processing, any volume
Built to complement, not replace existing systems
<2sIngestion Time
99.7%Uptime SLA
What Hindsait IDP Does
Five configurable capabilities. One intelligent platform.
User-configurable review, select the document types, sections, and data points your workflow needs. Every output is context-aware, clinically meaningful, and audit-ready.
Capture key clinical data across any document type, diagnoses, medications, lab results, vital signs, procedures, and more, with ICD-10, CPT, RxNorm, and SNOMED normalization applied automatically.
50+ clinical entity types
Diagnoses, medications, allergies, vitals, labs, procedures, clinical indicators, all in one pass
Standard coding mapped automatically
ICD-10, CPT, HCPCS, RxNorm, SNOMED, entities coded and normalized without manual mapping
Context preserved, not just terms
Negation detection, temporal relationships, and clinical context ensure extracted data reflects clinical reality
Generate concise, clinically meaningful summaries of complex multi-page records, in seconds. Summaries are aligned to the clinical workflow context: PA review, UM concurrent review, audit, or appeals.
Context-aware, not generic
Summaries reflect the clinical purpose, PA review, UM, audit, or appeals, not a generic document précis
48-page record → 4-sentence summary
Generative AI condenses complex narrative records into reviewer-ready summaries in under 30 seconds
Guideline-aligned output
Summaries structured to InterQual, MCG, or custom criteria, criteria flags surfaced automatically
Source-cited and auditable
Every summary statement linked back to source document page, section, and quote, full audit trail
AI Summary, PA Review ContextGenerated in 4.2s
Clinical Summary
Patient presents with community-acquired pneumonia (ICD-10 J18.9) with comorbid essential hypertension. Prior antibiotic course documented (Amoxicillin 500mg × 7 days, completed). Current admission warranted by persistent fever, elevated WBC (14.2), and documented oxygen saturation of 89% on room air.
Criteria Alignment
MCG: Pneumonia inpatientMET ✓
Oxygen criterion (<92%)MET ✓
Prior treatment failureMET ✓
Source pages citedpp. 3, 7, 11
Highlight & Compare
Instantly identify key data points and changes between document versions. Built specifically for appeals, audits, policy updates, and prior authorization resubmissions where version differences are clinically critical.
Side-by-side version comparison
Compare clinical record versions, policy revisions, or appeal submissions, changes highlighted automatically
Key data point highlighting
Diagnoses, lab values, medication changes, and clinical milestones highlighted within the document view
Appeals and audit support
Structured comparison reports document what changed, when it changed, and the clinical significance, ready for appeals submissions
Policy update tracking
Track changes in LCD/NCD coverage policies, InterQual criteria updates, and payor-specific PA requirements across versions
Compare: Initial versus Appeal Submission3 changes found
Initial (Denied)
Appeal (Updated)
O2 sat: 94%
O2 sat: 89% ← corrected
No prior Abx noted
Amox 500mg × 7d ← added
WBC: not documented
WBC: 14.2 ← extracted
Appeal recommendation: APPROVE, all 3 criteria now met
User-Configurable Review
Your clinical workflows are unique. Hindsait IDP is designed to be configured, not just deployed. Select the document types, sections, data points, and summary formats that match your specific review context.
Select document types and sections
Configure which document types to process and which sections to prioritize, specific to each workflow
Custom extraction templates
Define the specific data points, diagnoses, medications, labs, or custom clinical fields, for each use case
Guideline alignment selection
Align summaries and comparisons to InterQual, MCG, CMS LCD/NCD, or custom payor criteria per workflow
Output format and routing rules
Configure how outputs are structured, routed, and delivered, matching the downstream system that consumes them
Configuration Panel, PA WorkflowSaved
Document TypesRecords, Labs, Notes
Extract: Diagnoses✓ ON
Extract: Medications✓ ON
Extract: Lab Values✓ ON
Guideline AlignmentMCG + InterQual
Summary FormatPA Review Template
Output RouteUM Platform API
Configuration completeness100%
Seamless System Integration
Hindsait IDP outputs flow in real time into your existing clinical and administrative systems. Built to complement, not replace existing systems. No long implementation cycles. Connect once, extract everywhere.
Real-time API outputs
REST API delivers structured clinical data into claims, UM, prior-auth, audit, and BI systems in milliseconds
HL7 FHIR native
FHIR-compliant outputs for EMR, EHR, and payor platform integration, structured for clinical interoperability standards
SOC 2 + HITRUST CSF Certified
Enterprise-grade security infrastructure for PHI at every layer, transmission, storage, and processing
90-day to production
Most clients are in full production within 6 to 8 weeks, no multi-year implementation, no replacement of existing systems
Integration StatusAll Systems Live
Prior Auth Platform● Connected
Claims System● Connected
UM / Audit Platform● Connected
BI / Analytics● Connected
EMR / EHR (FHIR)● Connected
Avg. API response<200ms
SecuritySOC 2 + HITRUST CSF · HIPAA
The Value
Accelerating clinical intelligence across every decision workflow.
One platform. Every workflow where clinical documents determine outcomes, and speed and accuracy matter.
payor· Prior Authorization
PA Review & Automation
Clinical summaries and extraction delivered to reviewers before they open the case, reducing review time and improving first-pass approval rates.
3×Faster PA
+24%Approval Rate
MCG / InterQual criteria matching
Documentation gap detection before submission
CMS-0057-F compliant outputs
payor· Utilization Management
Concurrent & Retrospective UM
Real-time document processing delivers complete clinical context as records arrive, so faster concurrent review decisions and consistent retrospective analysis.
30%Efficiency
35%Cost Reduction
Level-of-care criteria matching
Clinical trajectory summarization
Discharge readiness indicators
payor· Payment Integrity
Clinical Audit & FWA Detection
Cross-reference claims against clinical records across your full population, identifying coding discrepancies, unsupported services, and FWA patterns automatically.
3×Audit Throughput
96%Coding Accuracy
HCC coding validation across your full population
Post-payment clinical review
Audit-ready finding documentation
Provider· Revenue Cycle
Denial Prevention & Appeals
Documentation gap detection before claim submission, and structured comparison reports for appeals that surface exactly what changed and why it now meets criteria.
↓Denial Rate
+24%First-Pass Rate
Pre-submission documentation scoring
Structured appeal comparison reports
payor-specific criteria matching
Provider· Population Health
Risk Adjustment & Quality
Surface HCC coding gaps, HEDIS and Stars measure opportunities, and SDOH risk signals from clinical records, across your entire member population.
↑ RAFRisk Adjustment
↑ StarsQuality Scores
HCC capture from unstructured records
HEDIS / MIPS / Stars gap identification
SDOH-aware risk stratification
Pharma· Market Access
Real-World Evidence & PA Support
Extract clinical evidence from unstructured records for HEOR, label expansions, and VBC contracting. Automate specialty drug PA documentation aligned to payor-specific criteria.
RWEUnlocked
100sPolicies Monitored
Formulary and step therapy criteria matching
payor policy monitoring
HEOR evidence extraction from records
Powered By
Four AI layers. One clinical intelligence engine.
Computer Vision
Document structure, layout & image analysis
→
OCR / OMR
Medical-grade optical character recognition
→
Clinical NLP
Context-aware clinical language understanding
→
Generative AI
Clinical summaries, context & reasoning
Integrates With
Real-time outputs into your existing systems.
Prior Auth Systems
Real-time PA workflow integration, structured clinical data delivered before review begins
UM Platforms
Concurrent and retrospective UM systems, extraction and summaries delivered as records arrive
Claims & Audit
Payment integrity and audit platforms, clinical evidence delivered for post-payment review
EMR / EHR (FHIR)
HL7 FHIR-compliant outputs for native EMR and EHR integration, no custom middleware
BI & Analytics
Population-level clinical data feeds into BI and analytics platforms for quality and risk reporting
Custom API
REST API for any downstream system, structured JSON outputs with <200ms response time
SOC 2 + HITRUST / HIPAA
CSF Certified security infrastructure, PHI protected at transmission, storage, and processing layers
6-8 Weeks to Production
Built to complement, not replace existing systems. Most clients are fully live in 6-8 weeks, meeting your infrastructure where it is
Get the Full Brief
Download the Hindsait IDP Product Brief & Case Study
Complete capability breakdown, technical specifications, integration guide, and a real-world case study showing 30% efficiency gain in medical review processing. Download begins immediately.
IDP Product Brief
Complete the form to unlock the full PDF
Download the IDP Product Brief
Full capability breakdown, technical specifications, integration guide, and case study. Your download begins immediately on submission.
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Ready to master the clinical data you already have?
Most clients are in full production within 6 to 8 weeks. See Hindsait IDP live with your own document types, faxed charts, scanned records, EMR exports, whatever you're working with today.
Provider Solutions
Audit-Proof · Risk-Adjusted
ACO / VBC Ready
Integrated RCM Intelligence for Providers & ACOs.
Prior Auth. Coding. Risk Adjustment. One platform.
Revenue cycle failure at the provider level isn't a billing problem, it's a clinical intelligence problem. Denials happen because PA submissions are incomplete. Coding errors happen because unstructured records aren't fully readable. Risk scores are inaccurate because HCC gaps aren't surfaced until it's too late.
Hindsait RCM solves all three with one integrated platform, automating prior authorization, AI-assisted and human-in-the-loop coding, and RAF score optimization across your entire patient population.
Hindsait RCM · Integrated Architecture
Order & Data Ingestion → Clinical Intelligence → Risk Optimization
Block 1: Audit Shield
Automated Prior-Auth
ICD-10 & CPT Extract
Payor Policy AI
API Submission
Secure Audit Vault
Evidence Log
Block 2: Smart Coding
Automated Coding
ICD-10 → HCC Crosswalk
Coding Gap Alerts
Human-in-the-Loop
MEAT Documentation
Validated Output
Block 3: Risk Intel
Population Health Views
RAF Score Calculator
HCC Mapping & Validation
Member Base RAF
Risk Benchmarking
Risk Dashboard
Clinical Notes
→
Audit Trail
→
Evidence Log
→
Submission & Reimbursement ✓
+24%PA ApprovalsFirst-pass rate
↓40%Coding BurdenAI-assisted HCC
100%Audit TrailRADV-ready
+24%First-Pass PA Approvalspayor-aligned submissions improve prior authorization approval rates on first submission
↓40%Coding Burden ReductionAI-assisted coding with human review reduces manual note documentation by up to 40%
RAF↑Risk Score AccuracyHCC crosswalk and gap identification closes coding gaps that leave legitimate risk scores uncaptured
100%Audit Trail CoverageImmutable, timestamped evidence log for every clinical decision, HIPAA compliant and RADV-ready
Platform Architecture
Three integrated building blocks. One audit-proof revenue cycle.
Each building block is a standalone capability, and a more powerful integrated system when deployed together. Clinical data flows from ingestion through coding through risk optimization in one continuous pipeline.
Building Block 01
Audit Proofing Shield
Automated Prior Auth · Secure Evidence Log · API Submission
Automated Prior Authorization
Extract ICD-10 and CPT codes from clinical records, match to payor-specific criteria, and submit via API integration, reducing manual submission effort entirely.
Real-Time Payor Policy Intelligence
Continuous web scraping of payor PA requirements, formulary changes, and coverage policy updates, so submissions always align to current payor expectations.
Confidence Scoring & Routing
Every PA request scored for evidence strength, high-confidence cases submitted automatically, borderline cases routed to clinical reviewers with full AI-surfaced context.
Secure Audit Vault
Every action logged, immutable, timestamped, HIPAA-compliant. The Authentic Evidence Log creates a permanent record of every authorized encounter and clinical decision.
+24% First-Pass Approval Rate
Building Block 02
Intelligent Coding & HCC Crosswalks
Automated + Human-in-the-Loop · ICD-10 to HCC · Validated Output
Automated Coding from Clinical Notes
Clinical NLP reads physician notes and extracts ICD-10 diagnoses, CPT procedures, and HCC-relevant conditions, coded automatically without manual chart review.
ICD-10 to HCC Crosswalk
Automated mapping from clinical diagnoses to Hierarchical Condition Categories, identifying coding gaps and surfacing underdocumented HCC conditions that affect RAF scores.
Human-in-the-Loop Review
Coders review AI-generated suggestions with full source evidence, accepting, modifying, or overriding with every decision traceable to the clinical record that supports it.
Validated & Audit-Proof Coding
Every code validated against source clinical evidence before submission, with full human authorization trail, RADV-ready documentation, and HCC compliance monitoring.
↓40% Coding Burden · HCC Compliance Monitored
Building Block 03
Risk Intelligence & Population Health
RAF Score Calculator · Population Views · Risk Benchmarking
RAF Score Calculator & Member Base RAF
Calculate and optimize Risk Adjustment Factor scores across your entire member/patient population, with validated risk scores, HCC mapping, and benchmark comparison.
Population Health Views
SDOH-aware population segmentation, chronic disease cohort analysis, HEDIS and Stars gap identification, all surfaced from clinical record extraction across your full population.
HCC Compliance Monitoring & Validation
Continuous monitoring of HCC coding accuracy, surfacing undercoded conditions, overcoding risks, and documentation gaps before CMS audit or RADV selection.
Risk Benchmarking & ACO Dashboard
Compare total RAF versus benchmark, track ACO and MSSP performance, and monitor shared savings risk, with real time dashboard visibility across your full practice or health system.
RAF Optimized · ACO Performance Tracked
Provider Prior Authorization
Stop denials before they leave your EHR.
PA denials are not a billing department problem, they are a documentation and intelligence problem. Hindsait RCM surfaces every criteria gap, every missing lab value, and every payor policy (monitored continuously by IntelliSync) change before your team submits a single request.
DENIED
15–20% YoY increase in PA denials across providers. Most are preventable, missing documentation that AI can detect before submission.
Hindsait: Documentation gaps flagged pre-submit
DELAYED
PA processing delays disrupt care delivery, consume clinical staff time, and slow revenue cycles, especially for high-cost specialty procedures.
Hindsait: API submission + confidence routing
Step 01
Clinical Record Ingestion & Extraction
Hindsait reads the full clinical record, EMR notes, labs, prior treatment history, and extracts ICD-10 diagnoses, CPT procedures, and the clinical evidence needed for the PA request.
96% Clinical NLP Accuracy
Step 02
Payor Policy Intelligence & Criteria Matching
Real-time payor policy intelligence matches the extracted clinical evidence against each payor's current PA requirements, flagging gaps and documentation deficiencies before submission.
Continuous Policy Monitoring · 100s of payors
Step 03
Confidence Scoring & Intelligent Routing
Every PA request receives a confidence score, high-confidence, criteria-complete requests route to automated API submission. Borderline cases are flagged for human clinical review with full evidence context.
Human-in-the-Loop for Complex Cases
Step 04
API Submission & Audit Trail
Approved PA requests are submitted automatically via API integration. Every action, extraction, scoring, review, submission, is logged to the Secure Audit Vault for appeals support and compliance documentation.
Immutable Log · Appeals-Ready · CMS-0057-F
PA Request - AI AnalysisCriteria Met ✓
Patient[Redacted] · Inpatient
Primary Dx (ICD-10)J18.9, CAP
Procedure (CPT)99232, Subsequent Hosp.
payorBlue Cross [Policy v4.2]
O2 Sat (criterion)89% ✓ (<92% met)
Prior TreatmentAmox 500mg ✓ (doc.)
WBC14.2 ✓ (elevated)
Documentation GapNone detected
Confidence Score96%
Routing to automated submission
All 3 MCG criteria satisfied · API submission queued
Intelligent Coding Platform
Automated coding + human judgment. Validated. Audit-proof.
The Hindsait coding platform is not a choose-one: automated or human. It's both, working in parallel. AI extracts and codes. Humans verify with source evidence. Every code is validated before it leaves the system. Every decision is traceable back to the clinical record that authorized it.
Automated AI Coding
Analyze Clinical Notes
Clinical NLP reads physician notes, discharge summaries, and operative reports, extracting diagnoses, procedures, and HCC-relevant conditions at full document fidelity.
ICD-10 to HCC Crosswalk
Every ICD-10 code automatically mapped to its corresponding HCC category, identifying gaps between what was coded and what the clinical record actually supports for RAF purposes.
Identify Coding Gaps
AI surfaces HCC conditions documented in clinical notes but not yet coded, chronic diagnoses that support risk adjustment but are missing from the current claim submission.
HCC Crosswalk, Live Mapping
E11.9
→
HCC 19
Type 2 Diabetes, major chronic condition
I50.9
→
HCC 85
Congestive Heart Failure, high RAF weight
N18.3
→
HCC 137
CKD Stage 3, comorbidity capture
GAP ⚠
→
HCC 18
Diabetes w/ complication, undercoded
HUMAN REVIEW
Human-in-the-Loop Validation
Human-in-the-Loop Review
Coders review AI-generated code suggestions alongside the supporting clinical evidence, accepting, modifying, or adding codes with every decision linked to source documentation.
Verify Source Evidence
One-click navigation to the exact page, section, and sentence in the clinical record that supports each code, eliminating chart-hunting and reducing reviewer time by up to 70%.
Authorized Encounter Confirmation
Every code receives human authorization, creating a legally defensible, RADV-ready evidence trail that links each diagnosis to the clinician, the encounter, and the supporting documentation.
Validated & Audit-Proof Output
Every code validated, every decision documented, every action timestamped, RADV-ready, SOC2 + HITRUST audited, and defensible.
Population risk optimization for ACOs & value-based care.
For Accountable Care Organizations, RAF score accuracy isn't a compliance checkbox, it's a shared savings calculation. Inaccurate risk scores mean inaccurate benchmarks. Inaccurate benchmarks mean lost revenue and misdirected care resources. Hindsait's Risk Intelligence platform closes both gaps.
RAF Score Calculator
Calculate individual and population-level RAF scores from clinical and claims data, with member-base RAF tracking, year-over-year trend analysis, and benchmark comparison against CMS and peer cohorts.
HCC Mapping & Gap Identification
Automated HCC mapping from clinical records identifies conditions that qualify for risk adjustment but haven't been coded, surfacing legitimate revenue opportunities while maintaining audit integrity.
Population Health Views & SDOH Analysis
Identify high-risk patient cohorts, chronic disease populations, and social determinant risk factors, so targeted care management interventions that improve outcomes and reduce total cost of care.
Risk Adjustment Benchmarking
Compare total RAF versus CMS benchmark and peer ACO performance, tracking shared savings risk, identifying performance gaps, and modeling the financial impact of improved coding capture.
Risk Dashboard, ACO PopulationLive
1.42Member Base RAF, Current Period
CMS Benchmark RAF1.38
RAF versus Benchmark+0.04 ↑
Total Members Scored12,847
HCC Gaps Identified284
HCC Gaps Closed (MTD)196 ✓
Est. Shared Savings RiskProtected ↑
RADV Audit StatusCompliant ✓
HCC Gap Closure Rate (MTD)69%
RAF versus Benchmark+2.9%
MEAT-Aligned Intelligence
Every HCC code, fully justified.
Hindsait surfaces M.E.A.T.-compliant evidence from clinical records automatically, so every HCC code you submit is linked to the documentation that defends it.
RADV-defensible from day one
Evidence Extraction
AI scans every chart for MEAT-qualifying language (vital signs, assessments, prescriptions, procedures), flagged and cited in seconds.
HCC-to-Document Linking
Every risk code is traced to its source record. No unsupported codes, no guesswork. Full evidence lineage for every chronic condition.
Coding Validation
Flags incomplete or unsupported codes before submission, reducing audit exposure and costly post-payment recoupment.
AI-Assisted Chart Review
Coders work faster with AI pre-surfacing the relevant documentation. Fewer missed HCCs, faster throughput, higher confidence on every encounter.
Permanent Evidence Log
Every action. Every decision. Immutable, timestamped, audit-ready.
Clinical Notes
Original clinical documentation, physician notes, labs, discharge summaries, stored as source evidence for every coding and PA decision.
Source of Truth
Audit Trail
Every action timestamped, extraction, scoring, human review, authorization, submission. A complete chain of custody for every clinical decision.
Chain of Custody
Permanent Evidence Log
Immutable record of every authorized encounter, HIPAA compliant, RADV-defensible, and timestamped so every HCC code has an unbroken evidence chain.
Immutable · HIPAA
Submission & Reimbursement
Validated claims submitted with complete coding, audit trail, and evidence log, maximizing clean claim rates and minimizing post-payment audit exposure.
Clean Claims · RADV-Ready
Who We Serve
Built for every provider organization facing revenue pressure.
From independent physician groups to large health systems and ACOs, Hindsait RCM addresses the prior authorization, coding, and risk adjustment challenges that directly affect financial performance.
Health Systems & Hospitals
Large Health Systems
Scale prior auth automation, coding intelligence, and HCC compliance monitoring across thousands of encounters per day, without adding headcount.
PA automation across all service lines
Enterprise coding platform with human review
Population-level HCC compliance monitoring
Integrated audit vault for all encounters
Explore Health System Solutions →
Physician Groups & Practices
Medical Groups & Practices
Reduce PA denial rates, cut documentation burden, and improve coding accuracy, giving physicians time back for patient care instead of administrative overhead.
EHR-integrated PA intelligence
Specialty-specific coding templates
Denial prevention and appeals support
Coding accuracy and HCC gap reports
Explore Medical Group Solutions →
ACOs & Value-Based Care
ACOs & MSSP Participants
Optimize RAF scores, close HCC coding gaps, monitor population health, and protect shared savings, with a complete risk intelligence platform built for value-based contracts.
RAF score calculator and member base tracking
HCC gap identification and closure workflow
Total RAF versus benchmark dashboards
RADV-ready audit trail and documentation
MSSP and VBC performance analytics
Explore ACO Solutions →
Get the Full Brief
Download the Hindsait RCM Product Brief & Case Study
Complete capability breakdown across prior authorization, coding platform, and RAF intelligence, plus implementation approach and measured outcomes from real provider deployments.
RCM Product Brief
Complete the form to unlock the full PDF
Download the RCM Product Brief
Platform architecture, capability breakdown, ACO RAF optimization framework, and implementation approach. Download begins immediately on submission.
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Ready to stop leaving revenue on the table?
Prior auth denials, coding gaps, and inaccurate risk scores cost provider organizations millions annually. See how Hindsait RCM closes all three, in one integrated, audit-proof platform.
About Hindsait
Built for the hardest problem in healthcare data.
Hindsait was founded in 2013 with a specific conviction: that the most consequential problems in healthcare (prior authorization delays, coding errors, avoidable denials, wasted clinical review time) were fundamentally data problems. Specifically, they were problems caused by unstructured clinical data that existing systems couldn't read.
Twelve years later, Hindsait has processed over 100 million clinical records, advanced production prior authorization workflows with WPS Health, and been recognized by Gartner as a 2026 Representative Vendor. The platform supports real prior authorization workflows with evidence-based, audit-ready clinical intelligence.
"Clinical records hold the truth about a patient's condition. For most of healthcare's history, that truth has been buried inside unstructured text, invisible to the systems making clinical and financial decisions. Surfacing it, reliably and at scale, is what Hindsait was built to do."
Pinaki Dasgupta, CEO & Founder, Hindsait
Our Mission
Hindsait exists to make clinical data accessible by turning unstructured records into structured intelligence that supports faster, more consistent, and defensible decisions. We built our platform specifically for healthcare, from the ground up, starting in 2013.
Our Expertise
Over 100 years of combined expertise across AI, engineering, data science, clinical informatics, and healthcare operations.
Our Impact
Live in Production at WPS Health, Gartner 2026 recognized, SOC 2 + HITRUST certified, serving health plans, providers, and ACOs nationwide.
The Team
Meet the people behind Hindsait.
Rocket scientists, clinicians, engineers, and data scientists, united by a single mission.
Pinaki Dasgupta
CEO & Founder
Pinaki founded Hindsait in 2013 after two decades shaping technology strategy and delivery at leading global IT firms, most recently as Managing Director at Accenture, where he led large-scale data and technology transformation programs across industries. That work brought him close to a problem healthcare had long accepted as unsolvable: clinical records full of critical information that the systems around them could not read. He founded Hindsait to solve it. He has led the company from inception through its production deployment at WPS Health, expansion of its prior authorization intelligence platform, and Gartner 2026 recognition. MBA.
Rebecca Gordon, MSN, RN
Chief of Health Informatics
As Patient Care Director at New York Presbyterian Hospital, Rebecca built direct experience with the documentation burdens that slow clinical decisions and increase administrative cost. She joined Hindsait to ensure the platform reflects clinical reality, not just data theory. Her background shapes how Hindsait approaches UM workflows, reviewer experience, and the design of human-in-the-loop processes. MSN, advanced study in Health IT.
Gopal Narayanan, PhD
Chief Technologist
Before joining Hindsait, Gopal was a Research Professor of Astronomy at UMass, where he developed the computational methods to process astronomical datasets at scales most systems couldn't handle, and used them to identify black holes and predict cosmic events. He brought that same discipline to healthcare: building the machine learning architecture that underpins Hindsait's clinical NLP, trained on over 100 million records. PhD in Astronomy, UMass Amherst.
Brian Zimmerman, MD
Chief Medical Officer
Dr. Zimmerman brings clinical practice, executive leadership, and deep UM expertise to Hindsait. His background in internal medicine, combined with years leading utilization management programs, means Hindsait's clinical review capabilities are designed around how physicians actually think, not how software engineers assume they do. Board-certified in internal medicine.
Shouvik Guha
Technology
Software engineer specializing in intelligent, data-driven systems for healthcare. Passionate about system design, automation, and document intelligence, transforming complex information into findings you can act on that improve clinical workflows.
Benjamin Becze
Technology
Discovered a passion for data and the stories it tells. B.S. in Data Science from UC San Diego. Joined Hindsait bringing machine learning and software development experience to the mission of improving healthcare through intelligent data systems.
Careers
We're Hiring.
We are looking for entry to mid-level Marketing professionals, Data Scientists, Developers, and UX Experts.
If you can write production-level code in Python, R, MapReduce, JavaScript, PostgreSQL, or NoSQL, or have experience in Marketing with tech or health-related startups, we want to hear from you.
Hindsait recognized in the Gartner® 2026 Market Guide for Intelligent Prior Authorization — live in production at WPS Health for prior authorization workflows.
411 Hackensack Avenue, Suite 200 Hackensack, NJ 07601
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See what 12 years of healthcare AI can do for your organization.
Production-deployed. Florida Blue-backed. SOC 2 + HITRUST certified. 100M+ records processed. 6 to 8 week deployment.
The Technology
One Platform. Three Products. Full-Stack Clinical Intelligence.
80% of clinical data lives in free text that most systems cannot read. Physician notes, discharge summaries, operative records, faxed documents. Hindsait reads all of it.
12+ years of healthcare-specific R&D produced three tightly integrated products, CNLP API, IDP, and IntelliSync, that together form a complete clinical document intelligence stack. From raw record ingestion to structured data output, policy-aware analysis, and seamless system integration. Twelve years of healthcare-specific training. Not adapted from somewhere else. Built from the ground up for healthcare.
CNLP API
Clinical NLP Engine
The foundation. 12+ years of healthcare-specific training. Extracts ICD-10/CPT, SNOMED, medications, labs, diagnoses, and much much more from any unstructured document.
↓ Foundation Layer
IDP
Intelligent Document Processor
The workflow layer. Configurable review, AI summarization, highlight & compare, prior auth package assembly, and real time API outputs into any downstream system.
↑ Workflow Layer
IntelliSync
Policy Intelligence Engine
The currency layer. Monitors 100s of regulatory sources, CMS, state Medicaid, NCCN, payor guidelines, continuously, so clinical criteria never goes stale.
↔ Currency Layer
Product 01 · Foundation Layer
CNLP API Clinical NLP Engine
At the foundation of every Hindsait product is its proprietary Clinical Natural Language Processing engine, built through more than a decade of rigorous training on healthcare-specific datasets. Unlike general-purpose NLP models, Hindsait's CNLP is purpose-built for the complexity and nuance of medical language. That depth of domain-specific training is the hardest asset to replicate in healthcare AI, and it cannot be compressed or shortcut.
Any accredited healthcare organization can securely upload medical records via API and receive a structured, machine-readable data feed in return, annotated, highlighted, and ready for downstream integration into claims, UM, PA, audit, or analytics systems.
What the API extracts:
ICD-10 / CPT codes & SNOMED terminology
Medications, dosages & prescription patterns
Lab values, vital signs & clinical quantities
Patient demographics & identifiers
Imaging, lab report & procedure tags
Surgical notes, screening & risk indicators, and more...
Key Technical Differentiators
Healthcare-Specific Depth
12+ years trained on real clinical data. Not a general NLP model adapted for healthcare, built specifically from the start.
Clinical Context Intelligence
Understands negation, temporal context, and clinical relationships, not just keyword matching. Reads records the way a clinician does.
Integration-First Design
Real-time API outputs connect to claims, UM, PA, EHR, and BI systems. Built to complement, not replace. 6–8 week deployment.
Proprietary Data Moat
100M+ records processed. Every customer and record improves the model, a compounding advantage no competitor can replicate.
The IDP is Hindsait's most configurable and user-facing product, designed to automate the complete lifecycle of clinical document intelligence. It sits above the CNLP API, consuming structured clinical data and converting it into workflows, summaries, comparisons, and system integrations. IDP doesn't just read documents. It understands them.
Configurable Review
Select exactly which document types, sections, and data points to analyze. Clinicians and informatics teams configure extraction templates, diagnoses, medications, lab values, criteria indicators, without engineering engagement.
AI Summarization
Generative AI condenses complex multi-page records into concise, clinically meaningful summaries aligned to the review context, PA, UM, audit, or appeals. Source-cited. Guideline-aligned. Audit-ready.
Precision Extraction
50+ clinical entity types extracted per document, diagnoses, medications, labs, procedures, vitals, with ICD-10, CPT, RxNorm, and SNOMED normalization applied automatically.
Highlight & Compare
Instantly identify key data points and changes between document versions. Built specifically for appeals, audits, and policy updates where version differences are clinically critical.
Real-Time API Integration
Structured outputs delivered in real time into claims, UM, PA, audit, EHR, and BI systems. HL7 FHIR-compliant. SOC 2 + HITRUST audited. <200ms API response.
IDP Integration TargetsAll Live
Claims Processing Systems● Connected
UM / Prior Authorization Platforms● Connected
Audit & Payment Integrity Systems● Connected
EHR / EMR (HL7 FHIR)● Connected
BI & Analytics Dashboards● Connected
95%
Extraction Accuracy
<30s
Per Document
80%
Less Review Time
Explore the full IDP platform
Capabilities, use cases, integration guide, and case study
Product 03 · Currency Layer
IntelliSync Policy Intelligence Engine
Policy documents arrive in an unmanaged torrent, PDF bulletins, HTML pages, Excel rate files, Word documents, posted irregularly by hundreds of government agencies, payors, and accreditation bodies. For compliance, UM, and claims teams, manual tracking is unsustainable. IntelliSync eliminates it entirely.
What manual tracking requires, that IntelliSync eliminates:
✗
Checking hundreds of websites manually
✗
Downloading and normalizing each new policy
✗
Reviewing line-by-line for changes
✗
Comparing prior versions for delta identification
✗
Updating internal systems and notifying relevant teams
What IntelliSync monitors automatically:
CMS LCD / NCD updates
All 50 state Medicaid agencies
NCCN / clinical guidelines
payor-specific PA policies
Excel rate files & structured data
Claims system propagation via API
99%+
Policy Intelligence Accuracy
On policy change detection across all monitored sources
5×
Productivity Gain
Per IntelliSync user versus manual policy monitoring teams
IntelliSync's Automated Workflow
1
Continuous Monitoring
Automatically scans 100s of regulatory sources, PDF, HTML, Excel, Word, at configurable frequency with zero human touches.
2
Change Detection & Normalization
Identifies new or revised policies, extracts the delta from prior versions, and normalizes into a structured, machine-readable format.
3
Stakeholder Notification
Alerts relevant teams, compliance, UM, claims, with structured summaries of what changed, what it affects, and what action is required.
4
System Propagation via API
Policy changes automatically propagate to claims adjudication rules, UM criteria, and PA decision logic via API, keeping operations current without manual updates.
Serves All Three Markets
payors:UM criteria currency, PA policy alignment, CMS compliance
Providers:payor-specific PA criteria, denial root-cause intelligence
Pharma:NCCN, FDA label updates, formulary changes, REMS monitoring
Platform Architecture
Full-stack clinical intelligence. Not a point solution.
Most healthcare AI vendors offer one of these capabilities in isolation. Hindsait is the only platform that combines all of them, from raw document ingestion through structured extraction, policy-aware analysis, and system integration.
Computer Vision
Document structure, layout analysis, and image classification from any source quality
OCR / OMR
Medical-grade optical character recognition including handwriting and fax reconstruction
Clinical NLP
12+ years of healthcare-specific language model training. Context, negation, temporal relationships
Generative AI
Clinical summarization, criteria narrative, and structured output generation
Hindsait versus the market
Capability
Hindsait
Cohere Health
Apixio
Availity
Healthcare-Specific CNLP (12+ yrs)
✓
✗
Partial
✗
Document Intelligence / IDP
✓
✗
✗
✗
Policy Intelligence (IntelliSync)
✓
✗
✗
✗
payor + Provider + Pharma
✓
payor only
payor only
Both
6 to 8 week deployment
✓
6 months
Unknown
Unknown
Utilization Management & Clinical Review
Clinical Review That's Consistent, Fast, and Defensible at Scale.
Every utilization review requires pulling the clinical record, finding the relevant findings, mapping them to criteria, and writing a rationale. That takes hours per case. Hindsait does the document work first, so reviewers start with the hard part already done.
53%Chart Review Time SavedDocumented across real UM and PA deployments using Hindsait
30%Medical Review Efficiency GainWPS Health Solutions, AI-assisted medical review processing
MinutesNot Hours Per CaseCNLP extraction reduces average chart review from hours to minutes
What Hindsait Does for UM
Every review type. Every stage. Fully supported.
Pre-Service Review
IDP processes submitted clinical records; CNLP extracts necessity indicators; AI generates a preliminary determination with supporting evidence, before the reviewer opens the case.
Concurrent Review
Real-time processing of updated clinical documentation during active inpatient admissions, keeping medical necessity determinations stay current as the patient's condition evolves.
Retrospective Review
Batch processing of historical records for post-service necessity determinations, DRG validation, and recoupment identification, at the population scale required for payor audit programs.
Criteria Currency via IntelliSync
MCG, InterQual, NCCN, CMS LCD/NCD, and payor-specific criteria are continuously monitored and updated by IntelliSync, so UM criteria is never stale, no manual tracking required.
MD Review Escalation Support
Complex and borderline cases are automatically escalated to physician reviewers, with all relevant clinical data pre-extracted, criteria pre-mapped, and evidence pre-organized. Reviewers decide faster with complete context.
Audit-Ready Documentation
Every UM determination generates a structured audit trail, extracted clinical indicators, applied criteria, reviewer actions, and AI-provided evidence. SOC 2 + HITRUST certified. Defensible under CMS, state, and accreditation review.
How Hindsait Transforms UM
From chart drop to determination, in minutes.
UM traditionally requires reviewers to manually navigate faxed records, locate relevant diagnoses, map them to criteria, and document a rationale, hours of work per case. Hindsait automates every step before the reviewer opens the record.
1
Records received & ingested
IDP accepts fax, PDF, EMR notes, HL7 FHIR, and any document format, automatically.
2
CNLP extracts clinical necessity indicators
Diagnoses, procedures, labs, medications, and clinical context extracted and structured in seconds.
3
Criteria applied automatically
Extracted data mapped against MCG, InterQual, NCCN, LCD/NCD, always current via IntelliSync.
4
AI generates determination with evidence
Clinically clear cases are evidence-matched for configurable workflow automation. Complex cases escalated to MD reviewers with complete pre-organized context.
5
Audit trail generated automatically
Every action, every evidence source, every criteria match documented, SOC 2 + HITRUST certified, defensible under any review.
See how Hindsait transforms clinical review for your organization.
53% review time saved. 6 to 8 week deployment. CNLP API + IDP + IntelliSync working together on your actual case types.
Hindsait CNLP credentials:12+ Years Healthcare-Specific Training100M+ Records ProcessedHITRUST CSF Certified · HIPAA + SOC 2Twelve years of healthcare-specific training.
CNLP API · Foundation Layer
The Clinical NLP Engine Healthcare Has Been Waiting For.
Upload medical records. Receive structured, machine-readable clinical data. Hindsait's CNLP API extracts ICD-10/CPT codes, SNOMED terminology, medications, labs, diagnoses, and 50+ clinical entity types, from any unstructured document, in seconds.
Not a general NLP model adapted for healthcare. Twelve years of healthcare-specific training. 12+ years of rigorous training on healthcare-specific datasets, built specifically for the complexity, nuance, and stakes of clinical language. The hardest asset in healthcare AI. Competitors cannot compress 12 years.
What the CNLP API Extracts
Send a record. Get structured clinical intelligence back.
Any accredited healthcare organization can securely submit medical records via API and receive a structured, machine-readable data feed, annotated, normalized, and ready for downstream integration.
Diagnoses & Codes
ICD-10 / CPT codes
SNOMED terminology codes
Clinical concept extraction
HCC risk adjustment codes
Medications & Labs
Medications, dosages, RxNorm
Lab values & vital signs
Prescription patterns
Allergy & contraindication flags
Procedures & Clinical
Imaging & lab report tags
Surgical notes & procedures
Screening & patient demographics
50+ clinical entity types total
Why CNLP API, Not Something Else
The moat that 12 years builds.
General-purpose NLP models can extract keywords. Hindsait's CNLP understands negation ("no evidence of pneumonia"), temporal context ("previously treated for"), clinical relationships ("secondary to"), and the semantic difference between a listed medication and an active prescription. That distinction matters in every clinical decision.
Healthcare-Specific Depth
Trained exclusively on clinical data, physician notes, discharge summaries, lab reports, operative notes, faxed records, not adapted from general text. Every model decision reflects healthcare context.
Clinical Context Intelligence
Handles negation, uncertainty, co-reference, and temporal reasoning, the linguistic complexities that cause general NLP to produce false positives in clinical review.
Compounding Data Moat
100M+ records processed since 2013. Every customer and every record improves the model. No competitor can replicate that training history, regardless of funding.
Integration-First Design
Real-time API with <200ms response. HL7 FHIR-compliant outputs. Connects directly to UM, PA, claims, EHR, and BI systems. Built to complement, not replace existing systems. Deployed in 6 to 8 weeks.
Frequently Asked Questions
CNLP API , Common Questions.
The CNLP API processes any clinical document type: physician notes, discharge summaries, operative reports, radiology and lab reports, pathology reports, faxed records, scanned handwritten notes, HL7 FHIR documents, and structured EMR exports. It supports PDF, image (TIFF, JPEG, PNG), plain text, HL7, and CCD/CCDA formats.
General LLMs are trained on broad internet text and adapted for healthcare as an afterthought. Hindsait's CNLP was trained exclusively on clinical documentation from 2013, physician notes, operative records, lab reports. It understands clinical negation ("no evidence of"), temporal context ("history of"), uncertainty markers, and co-reference resolution specific to medical language. General LLMs produce false positives in clinical settings that make them unsuitable for production decisions. Hindsait's CNLP is purpose-built for clinical evidence extraction and audit-ready prior authorization workflows, not generic text generation.
Standard clinical documents (1–30 pages) are processed in under 30 seconds, with API response times under 200ms for structured output delivery. Large chart packages (100+ pages) are processed in batch mode with real time status updates. The system scales horizontally to support population-level processing of thousands of records simultaneously.
The CNLP API is HITRUST CSF Certified, HIPAA compliant, and SOC 2 audited. All data is processed on HIPAA-compliant Google Cloud Platform infrastructure with end-to-end encryption in transit and at rest. BAA agreements are available for all healthcare customers. The API supports production prior authorization workflows at WPS Health, a leading Medicare Administrative Contractor.
The API is HL7 FHIR-compliant and delivers structured JSON output that connects directly to claims systems, UM/PA platforms, EHRs, audit systems, and BI dashboards. Integration is built to complement, not replace existing systems Most customers are live within 6 to 8 weeks. RESTful API with complete documentation and sandbox access available upon request.
The CNLP API is available to accredited healthcare organizations, health plans, Medicare Advantage plans, Medicaid MCOs, hospital systems, ACOs, physician groups, TPAs, health IT vendors, and pharmaceutical companies. Access requires a completed data use agreement and BAA. Contact info@hindsait.com or submit the demo request form to begin the access process.
Ready to access the CNLP API?
12+ years of healthcare-specific NLP. 100M+ records processed. Built for production prior authorization workflows. 6 to 8 week deployment.
Policy Changes Faster Than Teams Can Track. IntelliSync Never Misses One Change.
Coverage rules, fee schedules, and clinical criteria shift constantly across hundreds of agencies and payers. IntelliSync monitors every source, detects every change, and shows exactly what moved.
Policy updates arrive as PDFs, HTML pages, Excel rate files, and Word documents on irregular schedules across agencies, payers, and accreditation bodies. IntelliSync replaces manual tracking with continuous monitoring, exact version deltas, and criteria updates pushed into the systems that depend on them.
300+Regulatory Sources MonitoredCMS, all 50 state Medicaid agencies, payer medical policies, and clinical guideline bodies
99%+Change Detection AccuracySemantic comparison that knows a real policy change from formatting noise
5×Productivity Gain Per UserVersus the manual teams that monitor policy by hand
HITRUSTCSF Certified InfrastructureHIPAA and SOC 2, enterprise-grade security at every layer
The Problem
Manual policy tracking is a job that never ends.
Compliance, utilization management, and claims teams are expected to know the current rules at all times. But the rules live across hundreds of websites, each publishing on its own schedule, in its own format, with no notice when anything changes. The work is endless, and a single missed update can mean a denied claim, a failed audit, or a compliance penalty.
What manual tracking demands, that IntelliSync eliminates:
✗
Checking hundreds of agency and payer websites by hand
✗
Downloading and normalizing each new document, format by format
✗
Reading every revision line by line to find what changed
✗
Comparing against prior versions to isolate the real delta
✗
Updating internal systems and chasing down the teams who need to know
How IntelliSync Works
From published bulletin to updated system, automatically.
Four stages run continuously, with no human touches. IntelliSync watches the sources, isolates the change, summarizes what it means, and pushes the current criteria into the systems that act on it.
1
Continuous Monitoring
Scans hundreds of regulatory sources, PDF, HTML, Excel, and Word, on a configurable cadence, with no human checking required.
2
Change Detection & Normalization
Identifies new or revised policies, extracts the exact delta from prior versions, and normalizes it into a structured, machine-readable format.
3
Stakeholder Notification
Alerts the right teams, compliance, UM, and claims, with structured summaries of what changed, what it affects, and what action is required.
4
System Propagation via API
Policy changes propagate automatically into claims adjudication rules, UM criteria, and PA decision logic, keeping operations current without manual updates.
What IntelliSync Monitors
Every source that defines your rules.
Hundreds of government, payer, and clinical sources, every one tracked, categorized, tagged, and version-controlled.
CMS National Coverage
Local and national coverage determinations, transmittals, and CMS rule changes tracked at the source.
State Medicaid, All 50 States
Provider bulletins, manuals, and policy updates from every state Medicaid agency, each with its own format and schedule.
MAC Jurisdiction Bulletins
Medicare Administrative Contractor articles and jurisdiction-specific guidance, mapped to the regions they govern.
Commercial Payer Policies
Medical and pharmacy coverage policies across hundreds of commercial health plans, monitored for criteria shifts.
Clinical Guideline Bodies
NCCN and other evidence-based guideline updates, plus FDA label and REMS changes relevant to coverage.
Fee Schedules & Rate Files
Excel rate files, fee schedules, and structured pricing data, parsed and compared row by row across versions.
Core Capabilities
What IntelliSync actually does.
Continuous Source Monitoring
Scans every monitored source on a configurable cadence, handling PDF, HTML, Excel, Word, and dynamic viewers without manual intervention.
Semantic Change Detection
Goes beyond file comparison. Understands document structure to flag genuine policy changes and ignore timestamp and formatting noise.
Version Comparison & Highlighting
Side-by-side diff view with every addition and removal highlighted inline, so reviewers see exactly what moved between versions.
Delta Extraction & Normalization
Pulls the exact change from the prior version and normalizes it into a structured, machine-readable record with a plain-language summary.
Tagged, Searchable Policy Library
Every document categorized, tagged, and jurisdiction-mapped, with full version history and source lifecycle controls retained.
Alerting & API Propagation
Structured change alerts route to the right teams, and current criteria propagate automatically into claims, UM, and PA systems via API.
Who IntelliSync Serves
One engine. Current criteria for every part of healthcare.
For Payors
Health Plans & Payors
Keeps UM criteria current, holds PA policy aligned to the latest coverage rules, and maintains CMS compliance without a dedicated tracking team.
For Providers
Providers & Health Systems
Surfaces payer-specific PA criteria before submission and provides denial root-cause intelligence by tracking exactly when and how requirements shifted.
For Pharma
Pharma & Life Sciences
Monitors NCCN guidelines, FDA label updates, formulary changes, and REMS requirements across hundreds of plans for market access teams.
Stop chasing policy changes. Let IntelliSync bring them to you.
300+ sources monitored. 99%+ change detection accuracy. 6 to 8 week deployment alongside your existing systems.
Newsroom
News & Recognition
Press coverage, awards, and milestones from Hindsait's decade-long journey transforming healthcare with AI.
12+Years of coverage
25+Press features
2×Gartner recognized
/Healthbox
May 2015
Healthbox Chooses Hindsait as an Innovative Healthcare Company to Be Groomed for Scaling
Artificial intelligence and predictive analytics company Hindsait, Inc. is recognized by Healthbox and Florida Blue's parent GuideWell as an innovative health tech startup.
MIAMI, May 6, 2015 — After a rigorous, competitive process involving more than 50 healthcare startups, Healthbox and GuideWell announced the selection of Hindsait, Inc. to participate in their Miami Studio program. This selection distinguishes Hindsait as one of the elite in healthcare startups, recognizing them for their innovative technology that leverages big data with artificial intelligence and predictive analytics to improve healthcare.
As a result of their selection, Hindsait will receive support and guidance in the challenge of scaling its business throughout an eight-week program sponsored in large part by GuideWell, the parent of Florida Blue. Other program sponsors include Lake Nona Institute, the Health Foundation of Florida, and the John S. and James L. Knight Foundation.
Pinaki Dasgupta, Hindsait's CEO said, "Hindsait is excited to have been selected by Healthbox and GuideWell for the Miami Studio. We are pleased that they see Hindsait as we do: a company that can, at a large scale, provide innovative technology solutions for healthcare. Healthcare is just starting to recognize the power of artificial intelligence and predictive analytics to improve the health of our citizens and our healthcare system. There is so much potential to leverage big data with Hindsait's technology. We look forward to scaling our abilities to help healthcare payors, and providers improve patient outcomes and reduce costs."
Maria Siambekos, Vice President at Healthbox, said "We are excited to have the opportunity to work with some very talented entrepreneurs addressing significant challenges in healthcare through our new model. Helping these companies build scalable businesses is our key priority."
Healthbox is the preeminent source of healthcare innovation and drives actionable collaboration between inventors, entrepreneurs, and the healthcare industry.
About Healthbox
Healthbox is the preeminent source of healthcare innovation and drives actionable collaboration between inventors, entrepreneurs, and the healthcare industry. Our studio programs offer serious entrepreneurs the candid, unparalleled healthcare industry access and insight needed to succeed in a complex marketplace. We also partner with leading healthcare organizations to advance a culture of idea generation, business creation, and external collaboration. With operations in Boston, Chicago, Florida, Nashville, Salt Lake City, and London, Healthbox is building a strong, global community dedicated to driving change in healthcare. Healthbox has a portfolio of more than 75 active companies and strategic partnerships with more than 30 healthcare organizations.
About GuideWell
GuideWell Mutual Holding Corporation is a not-for-profit mutual holding company that is the parent to a family of forward-thinking companies focused on transforming health care. The GuideWell companies include: Florida Blue (Florida's Blue Cross and Blue Shield plan), GuideWell Health (a health care delivery company), GuideWell Connect (a health care consumer marketing company), and Diversified Service Options (an administrative and claims processing company for state and federal health care programs).
About Hindsait
Hindsait, Inc. turns artificial intelligence, predictive analytics, and big data into better healthcare at lower costs. Our SaaS platform takes in, rationalizes, and enhances complex healthcare data, then analyzes it to predict outcomes and help healthcare organizations and providers make better decisions more profitably.
See What Hindsait Can Do for Your Organization
From prior authorization to payment integrity: clinical intelligence built for production.
/Pilot Health Tech NYC
July 2014
Hindsait Wins Prestigious Pilot Health Tech NYC for Healthcare Innovation
Artificial intelligence and predictive analytics company Hindsait, Inc. is recognized as one of NYC's most promising healthcare technology startups.
NEW YORK CITY, July 2, 2014 — Announcing the selection of Hindsait, Inc. as a 2014 winner of Pilot Health Tech NYC. This selection distinguishes Hindsait as one of the area's elite health technology startups, recognizing them for their innovative technology that leverages big data with artificial intelligence and predictive analytics to improve healthcare.
As a result of their selection, Hindsait and host organization New York Blood Center (NYBC) will receive funding for a 2014 pilot program.
Beth Shaz, Chief Medical Officer of New York Blood Center, commented: "New York Blood Center is excited to partner with Hindsait, a leading healthcare artificial intelligence company..."
Pinaki Dasgupta, Hindsait's CEO, said, "Healthcare is just starting to use technologies like ours that use artificial intelligence and predictive analytics to improve our healthcare system and the health of our citizens. There is so much possibility to leverage these technologies along with big data to improve healthcare. Hindsait is proud to have been selected by Pilot Health Tech NYC's impressive panel of judges in what was a very competitive field. We look forward to helping healthcare payors, providers and organizations like New York Blood Center to improve patient outcomes and reduce costs."
Beth Shaz, Chief Medical Officer of New York Blood Center, commented: "New York Blood Center is excited to partner with Hindsait, a leading healthcare artificial intelligence company, in a new pilot to improve the health of New Yorkers. With this program, we aim to dramatically increase NYBC's number of African American blood donors. The pilot's success will make a significant difference in the health of African Americans who are now badly underrepresented among New York's blood donors."
Pilot Health Tech NYC awarded its first pilots in 2013 after being launched by The New York City Economic Development Corporation (NYCEDC) in partnership with Health 2.0. The program was launched to leverage the momentum of NY's health tech startups and to position New York City as the nation's hub for healthcare technology. One of the many signs of the program's success at selecting promising health tech startups is the recent investment by Google Ventures in Pilot Health Tech 2013 winner, Flatiron Health.
About Hindsait
Hindsait, Inc. turns artificial intelligence, predictive analytics and big data into better healthcare with a SaaS platform that helps healthcare organizations predict, manage and improve patient outcomes more profitably.
See What Hindsait Can Do for Your Organization
From prior authorization to payment integrity: clinical intelligence built for production.
Legal
Privacy Policy
How Hindsait collects, uses, and protects your personal information.
Last updated: September 24, 2019
Hindsait, Inc ("us", "we", or "our") operates https://hindsait.com (the "Site"). This page informs you of our policies regarding the collection, use and disclosure of Personal Information we receive from users of the Site. We use your Personal Information only for providing and improving the Site. By using the Site, you agree to the collection and use of information in accordance with this policy.
1
How and What Personal Information Is Collected
Use of the Site; Cookies. Hindsait collects Personal Information that you voluntarily provide us by completing and submitting forms on this Site, such as on the "Contact Us" page on the Site. This Personal Information may include information such as your name, email address, telephone number, company name and size, job title and the reason why you are contacting us. You may also use the site to apply for a job with us, in which case you will provide us Personal Information relevant to your job application.
The Site also automatically collects Personal Information through the use of cookies or similar technologies to facilitate and enhance your use of the Site and track usage patterns.
Essential Cookies
Facilitate your use and navigation of the Site. Includes session cookies, which are temporary cookies that remain in the cookie file of your browser until you close the browser.
Analytics Cookies
We and our service providers use analytics cookies that collect aggregated and/or anonymous information to analyze the performance of the Site. Users may opt out of Google Analytics at: policies.google.com/technologies/ads.
Third Party Marketing Cookies
These cookies collect information on your activities on the Site and other sites to display targeted marketing based on your interests.
Some browsers offer a "do not track" ("DNT") option. Because no common industry or legal standard for DNT has been adopted, we do not currently respond to DNT signals. You may elect not to accept cookies by changing your browser settings, though some features of our Site may not function without essential cookies.
2
How Information Is Used
We may use the Personal Information in one or more of the following ways:
Sending information or materials you request
Responding to your questions and concerns
Providing newsletter or marketing communications
Operating and improving the Site
Improving our products, services, and marketing
Conducting research and analysis
Evaluating your job application
Linking with third-party information to serve you better
3
Legal Basis for Processing
We will only process your Personal Information if we have one of the following legal bases to do so:
a
The processing is necessary to comply with our legal or regulatory obligations, such as tax reporting or regulatory requirements.
b
We have obtained your prior consent for processing your Personal Information for a specific purpose, such as evaluating your job application.
c
The processing is necessary for the legitimate interests of Hindsait, which are not overridden by your interests or fundamental rights and freedoms.
4
Duration of Processing Personal Data
Hindsait will store your Personal Information only for as long as is required to fulfil the purpose for which it was collected. If legal basis (b) — consent — applies, Hindsait will stop processing your Personal Information upon notification of your withdrawal of consent. Where Hindsait is required by law to retain your Personal Information longer, or where it is required to assert or defend against legal claims, Hindsait will retain your Personal Information until the end of the relevant retention period or until the claims in question have been settled.
5
Sharing and Disclosure of Information
Hindsait does not rent or sell your Personal Information. Hindsait does not share your Personal Information with third parties other than agents, contractors, and service providers who support our business and who are bound by contractual obligations to keep your Personal Information confidential.
We may disclose Personal Information if we believe it is necessary to: (i) comply with any court order, law or legal process; (ii) enforce or apply our Terms of Use; or (iii) protect and defend the rights or property of Hindsait. Hindsait may transfer your information to a buyer or successor in the event of a reorganization, merger, sale, or other disposition of Hindsait's assets.
6
Your Rights
You may opt out of receiving promotional emails from us by following the instructions in those emails. If you opt out, we may still send you non-promotional emails about our ongoing business relations.
Right to access and obtain a copy of your Personal Information
Right to request correction of inaccurate information
Right to object to processing of your Personal Information
Right to request erasure of your Personal Information
Right to request restriction of processing
Right to withdraw consent at any time
We will honor such requests as required under applicable data protection rules. These rights are not absolute and may be subject to exceptions.
7
Information Security
Hindsait takes seriously the security of your Personal Information. We implement technical and organizational measures to protect your Personal Information from unauthorized access, disclosure, alteration, or destruction.
You should be aware that we cannot guarantee that your Personal Information will never be accessed, disclosed, altered or destroyed in ways not described in this Privacy Policy. Third parties may unlawfully intercept or access transmissions or private communications.
8
Questions and Concerns
If you have any questions or concerns regarding the way we collect or handle your information, please contact us. We will take every privacy concern seriously and will assess it in a reasonably timely manner.
