Agent-ready context · Whole-person health

The health insights
your models are
missing.

contextRx.ai delivers proprietary predictive semantics — whole-person coaching outcomes, SDoH enrichment, and clinically-grounded risk signals — via secure API to payers, employers, and life sciences teams.

Request a Demo → See how it works
HITRUST CSF Certified Clinically Validated HIPAA Compliant
Risk Stratification
Precision
Multi-chronic and rising-risk cohort identification at population scale
Coverage confidenceHigh
Cohort Signals
Multi-chronic population detection
Rising-riskFlagged
Multi-morbidIdentified
High SDoH riskEnriched
Whole-Person Context
10k+ vars
Coaching + claims + SDoH, unified
How it works

Sovereign data. Curated insights.
Seamless Agent integration.

contextRx.ai wraps enriched outcomes data in a privacy-preserving compute architecture — so you get proprietary predictive context without raw data ever leaving a HITRUST-certified environment.

🏥
Sovereign Data Platform
Payer claims, coaching engagement, clinical notes, and 10,000+ variables remain locked inside a HITRUST-certified lakehouse. Raw data never moves.
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Privacy-Preserving Enclave
A hardware-rooted Trusted Execution Environment (TEE) applies differential privacy, semantic abstraction, and output truncation before any insight leaves the environment.
⚡
Proprietary Semantics Layer
A knowledge graph encoding conditions, comorbidities, SDoH barriers, interventions, and clinically-validated outcome edges — the core IP that powers every inference.
🌐
contextRx.ai API
Your team queries via REST or GraphQL. Receive risk scores, cohort explanations, SDoH-adjusted benchmarks, and natural-language context — no PHI, no re-identification risk.
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Sovereign Data Platform
Payer Claims Coaching Data 10k+ Variables Knowledge Graph Feature Store
One-way derivation pipelines
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Privacy-Preserving Enclave
TEE / Nitro Differential Privacy Watermarking Output Truncation
Encrypted internal calls only
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Serving Layer
API Gateway RAG Engine Model Inference Dashboard
HTTPS · OAuth2 · API Keys
🏢
Your Agents
Health Plans Employers Life Sciences Analytics Vendors
🔐 HITRUST CSF · 🛡 NIST · 📋 HIPAA BAA · 🔍 Audit Lineage
Products

Three ways to access
proprietary whole-person context

From black-box API inference to self-service dashboards, contextRx.ai meets your team where it works.

⚡
contextRx Insights API
REST + GraphQL endpoints for real-time cohort scoring, SDoH-adjusted risk, natural-language explanations, and "what-if" simulations. Embed predictive context directly into your population-health tools.
POST /v1/cohort/score · crx-v2
📊
Population Benchmarks
Pre-computed, privacy-noised dashboards showing outcomes by cohort type, SDoH risk tier, intervention intensity, and geography. Compare your population against clinically-validated benchmarks.
Quarterly · Real-world evidence
🤖
Semantic Search (RAG)
LLM-powered semantic search grounded in our proprietary knowledge graph. Query in natural language — receive structured, citable insights with no hallucination risk and no raw PHI exposure.
Grounded RAG · No raw PHI
Who we serve

Built for buyers who need
enriched, outcome-linked context

We partner with organizations that need the depth of whole-person coaching and claims linkage that traditional analytics platforms cannot provide.

01
Top Priority · Phase 1
Health Plans & Payers

Regional Blues, commercial payers, and Medicare Advantage plans seeking to enhance risk stratification, care management, and value-based care ROI — without rebuilding coaching infrastructure from scratch.

02
Strong Secondary · Phase 1
Large Self-Insured Employers

Fortune 500 and employer coalitions with 10k+ covered lives and rising chronic burden. White-label dashboards surface benchmarks for HR and benefits teams managing escalating cost trends.

03
High Upside · Phase 2
Life Sciences & Pharma

HEOR and RWE teams seeking enriched, longitudinal outcomes data on multi-chronic patients — lifestyle, medications, and SDoH — for post-approval evidence generation without raw PHI exposure.

04
Emerging · Selective
Analytics Vendors & ACOs

Care management vendors, value-based provider groups, and health equity consultancies seeking a best-in-class stratification layer as a white-label or API component for their own platforms.

Technology

2026-ready stack. Healthcare-grade
security from the ground up.

contextRx.ai is built on the emerging gold standard for healthcare data — compute-to-data, confidential computing, and semantic abstraction working in concert.

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Confidential Computing Enclave
Hardware-rooted TEE (AWS Nitro / Azure Confidential VMs) ensures queries execute on live semantics without ever exposing raw records to operators, customers, or attackers.
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Proprietary Knowledge Graph
Neo4j-powered graph encoding conditions, comorbidities, SDoH barriers, interventions, and clinically-validated outcome edges — weighted by real-world evidence, not assumptions.
🛡️
Differential Privacy + Watermarking
Calibrated noise injection on all aggregated outputs. Model watermarking and output truncation prevent extraction attacks while preserving statistical utility for inference.
📡
Grounded RAG Semantic Search
Vector DB + LLM grounded on our proprietary knowledge graph. Natural-language queries return cohort narratives, pathway logic, and SDoH-enriched predictors — no hallucination risk.
contextRx Insights API · v2
// Cohort risk scoring request
POST /v1/cohort/score
Authorization: Bearer <api_key>

{
  "population": "multi-chronic",
  "sdoh_layer": true,
  "model": "crx-v2",
  "conditions": ["diabetes", "depression"],
  "barriers": ["transportation"]
}
// 200 OK · 142ms
{
  "risk_score": 0.87,
  "savings_probability": 0.74,
  "cohort_context": "High SDoH + multi-morbid...",
  "phi_included": false
}
Trust & Compliance

Privacy isn't a footnote.
It's the architecture.

contextRx.ai is built for healthcare's highest trust standards. Security and compliance are not features — they are the foundation of every product decision.

🏆
HITRUST CSF
Healthcare Information Trust Alliance certification — stronger than baseline HIPAA requirements
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NIST Cybersecurity
NIST framework alignment with zero-trust network, mTLS between layers, no public data endpoints
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HIPAA BAA
Full Business Associate Agreements in place with all payer partners; de-identification validated
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Audit Lineage
Every semantic output traces to derivation logic via immutable audit logs — never to raw records
Raw data never leaves our environment. Only insights do.

contextRx.ai's core design principle: payer claims, coaching notes, and individual outcomes stay locked in our sovereign data platform. External parties interact exclusively with controlled, de-identified inference outputs.

  • Compute-to-data: queries execute inside a TEE enclave — we are the sole data contributor
  • Differential privacy noise applied to all aggregated outputs before external delivery
  • Model watermarking and output truncation prevent extraction attacks
  • Expert-determination de-identification validated and auditable — HIPAA Safe Harbor compliant
  • Automated end-to-end data lineage: output → derivation logic, never to individual records
Get started

See the context your
models are missing.

Schedule a 30-minute demo. We'll walk through your population, model your cohort opportunity, and show you exactly what contextRx.ai surfaces that your current analytics don't.

Request a Demo → Partnership inquiries