An AI-assisted verdict on the record — yours to approve, revise, or reject. ROADMAP
AI case merit assessment software, on the Medrecords AI roadmap, will build on Case Strength & Weakness Signal Flagging and Medical Literature Matching to render a scored, AI-assisted legal or clinical judgment. Every score ships labeled provisional until a licensed professional reviews, approves, and signs it off — the AI's judgment is never final on its own.
Built on cited signals and matched literature.
The assessment will not conjure a score from thin air. It weighs two inputs that already exist on the platform: the favorable and unfavorable fact patterns flagged in the record, and the guidelines and peer-reviewed sources matched to its diagnoses. Both are live today, and both are cited line by line.
A reasoning trail you can cross-examine.
A score no one can interrogate is a liability, not an asset. Every assessment will carry its full reasoning: which signals weighed in which direction, which literature informed the read, and where each input lives in the record. If you can't audit it, you can't sign it — so the audit trail is the product.
The sign-off gate is mandatory, not decorative.
Every assessment lands in a review state and stays there until the licensed professional acts: approve it as-is, revise it with their own judgment, or reject it outright. Until then the label reads "AI-assisted, provisional" — and no export, report, or downstream workflow treats the score as a final determination.
AI drafts the verdict. You render it.
Case merit and standard-of-care are professional judgments with professional consequences, and this feature is built to respect that line. The platform assembles the cited, auditable case for a conclusion; the licensed professional decides whether to adopt it. Audit-grade, source-linked, and legally defensible — because the human signature is structural, not cosmetic.
No automated claim decisions, no unsigned opinions, no score that quietly becomes a determination. That is the design, and it will not soften at launch.
How it will work.
Three steps, with the professional's decision as the only exit.
Strength and weakness signals are flagged and literature is matched — the two cited input layers, live today.
Case merit or standard-of-care deviation, labeled AI-assisted and provisional, with the full reasoning trail attached.
Approve, revise, or reject at the mandatory gate. Only a signed assessment ever moves downstream.
Who will sign the assessments.
The professionals whose judgment the gate protects.
Intake triage and case selection with a cited, provisional merit read — counsel decides.
For law firmsStandard-of-care deviation flagged with its literature basis — before the expert budget is spent.
For malpractice workA structured, cited clinical read to test their own conclusions against — then their signature.
For evaluatorsCase merit assessment, answered.
No — by design, never. Every assessment ships labeled "AI-assisted, provisional" behind a mandatory, visible sign-off gate: the licensed professional reviews the score and its reasoning, then approves, revises, or rejects it. Until that happens, nothing downstream treats the score as final. The AI's judgment is never final without the professional's sign-off.
Two live capabilities. Case Strength & Weakness Signal Flagging supplies the favorable and unfavorable fact patterns already flagged and cited in the record, and Medical Literature & Standard-of-Care Reference Matching supplies the guidelines and peer-reviewed sources matched to its diagnoses and treatment. The assessment layer weighs those cited inputs into a provisional score — it does not introduce new, unsourced facts.
Yes — that is the point of the design. Every score carries its full reasoning trail: which signals weighed in which direction, which literature informed the read, and where each input traces in the record. No black box: if you can't audit the reasoning, you can't responsibly sign it, so the reasoning is always on the table.
Same engine, two questions. Case merit asks a litigation question — how strong is this case on the record's facts — and is reviewed by counsel. Standard-of-care deviation asks a clinical question — does the documented care depart from applicable guidance — and is reviewed by a qualified clinician. In both modes the output is provisional until the right professional signs off.
AI Case Merit & Standard-of-Care Assessment is on the roadmap and not yet generally available. Use the "Get notified" button to leave your email and we will contact you at launch. The two capabilities it builds on — signal flagging and literature matching — are the place to start today.
Related capabilities.
The cited layers underneath the score — live today.
Favorable and unfavorable fact patterns flagged in the record, cited — signals, not a verdict.
ExploreGuidelines and peer-reviewed sources matched to the record's diagnoses — unsigned reference, cited both ways.
ExploreSuccess and value ranges from comparable resolved cases — every driver cited to your record.
ExploreBe first in line when assessment opens up.
Case merit and standard-of-care assessment is on the roadmap. Leave your email for launch — or book a demo of the cited signal and literature layers it builds on, live today.