Reveleer vs Xsolis (2026)

AI Health Index verifiedAugust 4, 2026
Verdict

Two platforms bought by the same risk bearing organisation for different parts of the year. Reveleer works retrospectively, retrieving records, parsing charts and populating risk adjustment and quality submissions, which is how a contract year gets closed once the visits are gone. Xsolis works in the moment, scoring medical necessity continuously between payer and provider so both sides argue from the same number, with peer reviewed research behind that score and the strongest security posture in this part of the index. They are not alternatives. What they share is an unanswered question apiece: Reveleer should be asked its ratio of codes removed to codes added, and Xsolis the proportion of AI informed adverse determinations overturned on appeal. Those two numbers describe whether either system is calibrated or merely productive.

The case for Reveleer
  • It works after the encounter, retrieving records, parsing charts and populating both risk adjustment and quality submissions, which is the machinery that closes a contract year.
  • Retrieval is the hard part of retrospective work and it owns that step rather than assuming charts arrive.
  • Quality reporting sits alongside risk adjustment in one platform, so a single workflow serves two regulatory obligations.
The case for Xsolis
  • It sits between payer and provider rather than serving one side, scoring medical necessity continuously so both parties argue from the same number.
  • It is the only vendor in that cluster with peer reviewed research behind its score, published across multiple health systems.
  • A risk based certification at the two year tier is the strongest security posture in this part of the index.

This comparison is published by AI Health Index, an independent research platform that compares healthcare AI vendors objectively. Reveleer and Xsolis 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

At a Glance

Plain facts

Fact Reveleer Xsolis
Primary category Value Based Care Intelligence RCM & Prior Auth AI
Founded 2009 Not recorded
Headquarters Glendale, California, United States Franklin, Tennessee
Website reveleer.com xsolis.com
Attribute Matrix

Side by Side

Axis
R
Reveleer
X
Xsolis
AI Centrality
Autonomy and Oversight Model
Model and Technology Transparency
Model Supply Chain Disclosure
Clinical and Operational Evidence
AI Safety and PHI Stewardship
HIPAA and BAA Posture
Security Certifications and Trust Center
FDA and Regulatory Status
AI Governance and Bias Disclosure
AI Liability and Recourse
EHR and Interoperability Depth
Deployment Model and Data Residency
Commercial Transparency
Setting and Specialty Coverage
Citable Summaries

Each record in one paragraph

Written to be quoted whole. Each paragraph states what the AI Health Index verified about the vendor, with the caveats attached. Generated from this pair’s live capability grades, so it moves when a grade moves.

Reveleer

The AI Health Index records no top capability grade for Reveleer on any axis it scores. Set against Xsolis, Reveleer grades higher on FDA and Regulatory Status. Its thinnest published disclosure sits on Model Supply Chain Disclosure. Grades reflect evidence the AI Health Index could verify at the last review, so a low grade records disclosure the vendor has not published rather than a capability it has been shown to lack.

Source: AI Health Index, August 2026

Xsolis

The AI Health Index awards Xsolis its top capability grade on several axes, including AI Centrality, Autonomy and Oversight Model and Clinical and Operational Evidence. Set against Reveleer, Xsolis grades higher on several axes, including AI Centrality, Autonomy and Oversight Model and Model and Technology Transparency. Grades reflect evidence the AI Health Index could verify at the last review, so a low grade records disclosure the vendor has not published rather than a capability it has been shown to lack.

Source: AI Health Index, August 2026

FAQ

Questions buyers ask

Should we choose Reveleer or Xsolis?

On the axes where the AI Health Index separates them, Reveleer grades higher on FDA and Regulatory Status, and Xsolis grades higher on several axes, including AI Centrality, Autonomy and Oversight Model and Model and Technology Transparency. Xsolis leads on the greater share of scored axes, but the split means the decision turns on which constraint is binding rather than on an overall winner.

Where do Reveleer and Xsolis differ most?

The widest separation the AI Health Index records between Reveleer and Xsolis is on Clinical and Operational Evidence, where Reveleer grades C and Xsolis grades A. That axis sits in the AI Capability group, so it should carry the most weight for a buyer whose binding constraint is how much of the work the model itself is trusted to do.

Where do Reveleer and Xsolis grade the same?

The AI Health Index grades Reveleer and Xsolis the same on AI Governance and Bias Disclosure, Deployment Model and Data Residency and Commercial Transparency. Neither holds an advantage the index can evidence on those axes, so they should not carry weight in a selection between these two.

What have Reveleer and Xsolis not disclosed?

At the last review, at least one of Reveleer and Xsolis published thin or absent detail on Model Supply Chain Disclosure. The AI Health Index treats an absent disclosure as a gap in the public record rather than a failure of the product, so these are the axes to get in writing during diligence instead of inferring from the grade.

Keep Comparing

Related comparisons

Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Value Based Care Intelligence page.

Disclosure

These serve adjacent functions inside a risk bearing organisation and neither publishes the number its own category most needs. For retrospective risk adjustment that is the ratio of codes removed to codes added, since a platform tuned to find more and one tuned to find correctly look identical on every reported metric. For utilization management it is the proportion of AI informed adverse determinations overturned on appeal. Neither vendor publishes a bias evaluation or subgroup analysis, which matters most in the lane where an output can end in care denied.