Speak Your Notes. AI Writes the Record.
AI Scribe is being validated for turning consultation audio into SOAP-note drafts, referral-letter drafts and visit summaries for clinician review. Each institution verifies the supported capture, export or EMR writeback path before use. Validation covers 50+ languages, including Bahasa Indonesia, English, Malay, Mandarin, Cantonese and Tamil.
From Voice to Connected Encounter Context
The validation workflow moves from speech to structured encounter context and clinician review. Export, integration and writeback are enabled only through a path that the institution has verified and approved.
Voice Recording
Physicians speak naturally during or after consultation. No scripting or structured commands required.
Multilingual ASR
State-of-the-art ASR transcribes speech in Indonesian, English, Cantonese, Mandarin, Malay, Tamil, and more.
Structured Encounter Context
Transcribed text is structured into a clinical encounter — assessment, plan, problems and coding-ready detail. A SOAP note is one of several formats; referral letters and visit summaries are others.
ICD Coding
AI can suggest ICD-10 candidates from the note draft. Physicians review and confirm any code before it is used.
Writeback & Routing
After clinician approval, the institution can validate an API, HL7 FHIR, controlled integration or structured-export path. Writeback is used only where that path is supported and approved; the HIS/EMR remains the source of record.
Clinical Documentation, Reimagined
Designed for real clinical workflows: structured note drafts and coding candidates for clinician review, with the final format and system path validated by each institution.
Multilingual ASR
The 50+ language validation set includes Indonesian, English, Cantonese, Mandarin, Malay and Tamil. Exact language and code-switching performance is verified for the institution's use case.
Cantonese ASR — 95%+ internal benchmark accuracy
Cantonese transcription reaches 95%+ accuracy on our internal medical dataset and handles natural code-switching the way clinicians speak.
Structured Encounter Context
The draft can organize assessment, plan, problems and coding detail as a SOAP note, visit summary or referral letter. Approved context can support other Micromeet workflows where the institution has enabled that connection.
ICD-10 Coding Suggestions
The validation workflow can surface ICD-10 candidates from a note draft. Physicians review and select any code before use: AI prepares, the clinician decides.
A path verified for your systems
The team evaluates customer-authorized API, HL7 FHIR, Agent Browser and structured-export options with each institution. The supported workflow and production readiness must be verified before deployment.
Clinician-confirmed and governed
The clinician reviews and confirms every note draft, and clinical responsibility remains with the clinician. Templates and workflow settings are changed through governed configuration and evaluation, not autonomous learning from each case.
Wherever Your Clinicians Document
Early validation covers consultation and reporting workflows; each in-scope clinical draft is reviewed by a clinician, and each enabled downstream path is confirmed by the institution.
General Practitioners
Pilot workflows evaluate how consultation audio can become a review-ready note draft while the clinician remains responsible for the final record.
Specialists & complex reports
Specialists can test structured drafts for complex cases and report findings, with coding candidates and clinical content reviewed before use.
Across the institution
Approved encounter context can be routed to supported AI Care Command Center or Care Loop workflows where the institution has verified that connection. Any future Claim Readiness handoff would require separate validation and enablement.
Built for the way clinicians actually speak
Natural medical speech across 50+ languages — including the mixed-language, code-switching consultations clinicians have every day. As evidence of that range, Cantonese — one of the harder languages for speech recognition — reaches 95%+ accuracy on our internal medical dataset.(Internal dataset)
Micromeet — AI for governed healthcare
See AI Scribe in action
Review the validation workflow and the integration options that would need to be verified for your clinical and HIS environment.