The model layer

Six models. One clinical record.

A named, versioned model layer, not one prompt behind a chat box. Each model does one job. Together they make up the agents.

The six

Each one does a job you can name.

Speech becomes a note, the note becomes code, and the code becomes a score, an answer and a proposed action.

01: Language to code

IASORA Lex

A note only becomes clinical data when something can name the code and defend it.

Codes to

SNOMED CT · ICD-10 · LOINC · RxNorm · CPT

Extracts

Conditions, medications, allergies, procedures, observations

Resolves

Abbreviations, negation, disambiguation, specialty context, confidence thresholds

Reads

Scribe notes, referral letters, uploaded documents

The agent workforce

Each agent works next to a person.

An agent chains these models for one job. It prepares the work; the person beside it decides. Any model can also be licensed on its own.

Patient

AI Call Operator

Answers and makes patient calls, and books against live availability.

VoiceReason

Care coordinator

Care Gap Closure

Finds who is overdue for care, and reaches out to them.

LexVoiceReason

Practice manager

No-Show Prevention

Reminds patients before the visit, so fewer appointments are missed.

ScribeVoiceQL

Clinician

Medication Reconciliation

Checks the medication list against what was said and prescribed.

LexScribeRiskReason

Clinical director

Risk Stratification

Stratifies the panel and measures the outcome.

RiskQLReason

Leadership

Ask Your Data

Answers questions about your patients and performance in plain language.

QLReason

Whichever agent runs, the run is the same six steps

01CaptureA consultation, a call, a documentScribe · Voice
02CodeLanguage becomes coded, structured dataLex
03ScoreThe patient is re-scored, every point traceableRisk
04ProposeThe agent drafts the action, with its evidenceReason
05 · GateA person approvesNothing reaches the chart unapprovedHuman decision
06MeasureCounted in English, over the live recordQL

Every step is one authorised, metered and logged call against your workspace.

How they run

Every call is authorised, metered and logged.

The model layer sits behind one gateway: one place where access, cost, residency and audit are decided.

On or off, per workspace

Switch each model on for a workspace at a tier, or leave it off. A clinic that wants only the scribe gets only the scribe.

Metered to the action

Every call is priced and counted where it happened, so each AI action has a cost next to the work it did.

Logged, every request

Which model, workspace and user, what it was asked and what it returned. Written whether or not anyone is looking.

Inference stays in region

Kept inside your jurisdiction, on private cloud or on-premise including air-gapped, for health systems that cannot send data out.

Bring your own keys

Run the layer on your own model credentials, and keep the routing, metering and audit.

Versioned, and reversible

Weights, thresholds and rules change under an audit diff. A change that does not hold up rolls back in one step.

Where the models show up in the product

Scribe and Voice in the consultation and at the front desk, Lex on every document, Risk across the panel, QL in Analytics Studio, and Reason inside every agent.

See the platform

Get started

Run one model, or the whole layer.

Use the scribe on your own consultations, or talk to us about the model layer inside your own estate.