Navina vs Reveleer: prospective and retrospective risk adjustment in 2026.

The real distinction

People search "Navina vs Reveleer" expecting two products that do the same job better or worse than each other. They do not compete. Navina works before the encounter; Reveleer works after it. One puts a suspected condition in front of a clinician while the patient is still in the room. The other reads charts that have already been written, validates the evidence, and packages it for audit.

Risk adjustment has two halves. Prospective capture documents conditions accurately at the time of the visit, so the diagnosis is supported in the medical record when it is submitted. Retrospective review checks what was captured, finds what was missed, and assembles defensible evidence for the Risk Adjustment Data Validation audit. Choosing between Navina and Reveleer usually means you have misframed the question. The right question is which half of your program is weaker right now.

Comparison at a glance

The table below maps each tool to where it runs and what it is built to do. Categories are descriptive, not pejorative: prospective detection and retrospective validation are complementary, and many organizations run both.

How to choose

1. Where is your gap, before or after the visit?

If conditions are getting missed in the exam room because clinicians lack a clear, summarized view of the patient at the moment of care, that is a prospective problem, and a point-of-care copilot is the fix. If conditions are documented but your evidence is thin, your submissions are incomplete, or you are exposed at audit, that is a retrospective problem. Diagnose the gap first, then pick the tool that closes it.

2. Point-of-care fit vs. chart-review volume

Prospective tools live in the clinician's workflow and are judged on whether they reduce documentation burden while improving capture accuracy. Retrospective tools are judged on throughput and accuracy across large volumes of charts. These are different engineering problems and different procurement criteria. A tool optimized for one is rarely optimized for the other.

3. RADV defensibility

Under CMS rules, captured conditions must be supported by the medical record, and audits can recover payment for diagnoses that are not. Prospective capture improves defensibility at the source by tying the diagnosis to documentation during the visit. Retrospective review and submission tooling assembles the evidence packages auditors expect. See the latest CMS risk adjustment guidance and ongoing rulemaking on the CMS Federal Register page for current requirements, and our RADV-defensible HCC guide for how to build a capture program that holds up.

4. How fast it gets to a measurable outcome

Ask each vendor for a specific date when a measurable result appears, not a go-live date. Both prospective and retrospective tools typically deploy in weeks to months, but the value shows up in different places: fewer missed conditions at the visit, or a cleaner, more complete submission and audit file.

Navina

Navina is a clinician-first AI copilot. It pulls patient data from the EHR, health information exchange, and claims, then summarizes it and surfaces suspected conditions and care-gap evidence at the point of care, with one-click documentation inside the chart. For physician groups and ACOs whose primary lever is what happens during the visit, Navina is well designed: it puts the right context in front of the clinician at the moment the diagnosis can be made and documented. Its focus is the exam room and the clinician, rather than the high-volume chart-review and audit-submission work that happens after the encounter.

Reveleer

Reveleer is built for high-volume retrospective work. Its Evidence Validation Engine automates chart retrieval, parses records, and populates abstraction fields for review, supporting both HEDIS quality abstraction and RADV or IVA submissions. For a plan that needs to run large chart-review and audit-submission programs accurately and on time, Reveleer is a strong fit. Its strength is extraction, validation, and review of data that has already arrived, which is exactly what the audit half of risk adjustment requires. It is not designed to act in the exam room before the encounter is documented.

Where an AI execution layer fits

Navina and Reveleer are each strong at their half. The gap most risk-bearing organizations feel is the seam between them: a condition flagged prospectively still has to be acted on, documented, and later validated, and that handoff is where work falls through. Detection and validation both tell you something. Neither, on its own, closes the loop in real time.

Pelica is the execution layer that runs both halves in one canonical record per member, built from claims, EHR, pharmacy, lab, ADT, and payer feeds. The Risk Adjustment Copilot does real-time HCC capture with trumping logic applied and an audit-defensible chain of custody, so prospective detection and retrospective validation live on the same record rather than in two disconnected tools. On top of that record is an action layer: outbound voice, EMR overlays, a provider portal, and a coder workspace, plus agents that operate payer portals and EHRs the way a person would. The point is not only to detect the condition or validate it later. It is to act on it, make the call, book the visit, and prepare the evidence.

None of this makes prospective or retrospective tools wrong. If your only weak half is point-of-care capture, a clinician copilot may be enough. If it is audit and submission, a chart-review engine may be enough. But if both halves are weak, or if the handoff between them is where conditions go uncaptured, an execution layer that does the work across both is the higher-leverage purchase, and it deploys in weeks rather than quarters.

The buyer is not choosing detection or validation. The buyer is asking who closes the loop in real time.

Sources

• CMS: Medicare Advantage risk adjustment
• CMS rulemaking and notices, Federal Register