Navina vs Pearl Health (2026)
Both help a provider group succeed under risk and they intervene at different moments. Navina works at the point of care, assembling a patient portrait from the record, health information exchanges, claims and care gap files and surfacing suspected conditions with the evidence attached, so the clinician acts during the appointment. Pearl works before it, predicting which Medicare patients are heading for avoidable cost so care teams can reach them first, across thousands of providers and hundreds of thousands of attributed beneficiaries. If your gap is that clinicians finish visits without addressing what mattered, Navina is aimed at that and has the stronger named security position. If your gap is that nobody knows which patients to call this week, Pearl is built for that. Both should be asked what proportion of the conditions they surface clinicians actually confirm.
- It works inside the visit rather than around it. A consolidated patient portrait is assembled from the record, exchanges, claims and care gap files and presented at the point of care, with every insight carrying the evidence behind it.
- The security position is named and typed: ISO 27001 and SOC 2 Type II with the type stated, where the alternative publishes a certification announcement without an equivalent named attestation set.
- Bidirectional native integration is the delivery mechanism rather than a claim, which is what determines whether a clinician sees the insight during the appointment or after it.
- Scope is stated clearly and matched to a real program: Medicare populations, primary care providers and risk bearing arrangements, rather than value based care in general.
- Scale is documented, with thousands of providers and hundreds of thousands of attributed beneficiaries, so the predictive prioritization has been exercised against a large real population.
- Prioritisation is the product rather than a feature: it identifies which patients to reach this week, which is the operational question a small primary care practice under risk actually has.
This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Navina and Pearl Health are each graded against the same capability taxonomy, from each vendor's own public materials and the regulatory record, under the AI Health Index verification standard. No vendor pays for placement, and no vendor has reviewed this page. How this evidence is graded
Plain facts
| Fact | Navina | Pearl Health |
|---|---|---|
| Primary category | Clinical Decision Support | Value Based Care Intelligence |
| Founded | 2018 | Not recorded |
| Headquarters | New York, New York, United States | New York, New York |
| Website | navina.ai | pearlhealth.com |
Side by Side
Select any grade to read the note behind it.
Each vendor in one paragraph
Written to be quoted whole. Each paragraph opens the AI Health Index profile of the vendor: what the product is, who buys it and what it does.
Clinician copilot that ingests data across the EHR, health information exchanges, insurance claims, and care gap files, then uses proprietary language models to classify documents and extract structure from free text, producing a consolidated Patient Portrait at the point of care. Surfaces suspected chronic conditions never explicitly documented, infers hierarchical condition categories for risk adjustment, and supports HEDIS care gap closure, with every insight linked back to the underlying clinical evidence.
Source: AI Health Index, September 2026
Pearl Health is a New York value based care enablement company for Medicare primary care. Its platform analyses claims, ADT feeds and record system data to rank the patients who need attention first, suggests next steps such as follow ups and diagnosis gaps, automates routine outreach and scheduling, and tracks cost, quality and benchmark performance; its actuarial and data science teams match practices to the Medicare program and risk level that suits them across ACO REACH, MSSP and Medicare Advantage.
Source: AI Health Index, September 2026
Questions buyers ask
How do Navina and Pearl Health handle patient data?
For Navina, data processed on behalf of a customer is retained for as long as the service runs and a reasonable time after; data is stored on AWS in North Virginia; and information the company anonymizes or de identifies may be used and disclosed to third parties without restriction, including to improve its services. The core technology page adds that Navina is built with strict data governance, HIPAA compliance and encryption.
With Pearl Health, the company's HITRUST announcement says the certification validates the security and privacy measures protecting the patient data entrusted to it by customers and partners; the privacy policy says it may anonymize and aggregate information for analytics and reporting but covers only the website and excludes the secure platform. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified September 22, 2026. No vendor pays for placement.
Which settings and specialties do Navina and Pearl Health cover?
In Navina's case, the value based tie is the product itself: HCC risk adjustment and RAF accuracy, HEDIS quality measures and care gap closure, and analytics tracking value based performance, with the FAQ covering risk adjustment audits for Medicare Advantage plans. The company has extended into ambient transcription combined with historical data, widening from a pre visit tool toward the full encounter.
For Pearl Health, the scope is Medicare primary care: health systems, physician networks and independent practices in ACO REACH, MSSP and Medicare Advantage, with the company reporting 250,000 beneficiaries, 10,000 providers and more than 40 states. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified September 22, 2026. No vendor pays for placement.
What evidence is published for Navina and Pearl Health?
With Navina, the headline claims are about risk adjustment and diagnosis: 500,000 previously undocumented conditions identified in the last 12 months, a 77 percent acceptance rate for the inference engine, and customer figures such as more diagnoses per visit and higher risk scores.
In Pearl Health's case, customers quoted by name include BayCare Health System, Holzer Health System, Santé Physicians, Hudson Headwaters, PraxisCare, MDX Hawaii, Virginia Care Partners, BlueSky MD and Odibo Medical Group. The company is the claimed source, and no baseline, period, population or method accompanies the figures; the quotes describe the partnership rather than measured outcomes. From the AI Health Index, drawn from each vendor's own published materials and the regulatory record, verified September 22, 2026. No vendor pays for placement.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers.
Both vendors surface conditions and care gaps that improve documentation completeness and also raise risk adjusted revenue, and neither publishes how it separates the clinical benefit from the coding benefit or what proportion of surfaced suspected conditions clinicians confirm. That confirmation rate is the number to ask for, since a model tuned to surface more suspicions looks identical to a model tuned to surface better ones on every metric either vendor reports.
Neither publishes a governance framework, model documentation or subgroup analysis. Pearl publishes no retention position, training use statement or de identification posture. Navina publishes no pricing and states only that data rests on AWS in North Virginia.