Medical AI company
Suki
Ambient clinical intelligence platform for documentation, dictation, coding and orders, integrated with major EHRs.
Company overview
Suki builds an ambient clinical intelligence platform that captures patient conversations to generate notes, patient instructions and orders. It also offers AI dictation and supports coding and revenue workflows. The platform integrates with major EHRs. Its listed address is in Redwood City, California.
- Headquarters
- Redwood City, United States
- Company type
- AI Technology Developer
- Deployment
- EHR-integrated
In its own words: “Our mission is simple: to create ambient intelligence that assists clinicians, so they can focus on what matters most.” source
AI products and platforms
- Suki Ambient DocumentationAI-powered
Captures the patient conversation to generate notes, patient instructions and orders
Product page ↗ - Suki DictationAI-powered
Voice dictation solution for clinicians
Product page ↗
Technology categories
Clinical applications
- ambient documentation
- dictation
- coding
Official sources
Last verified 29 October 2026 against the sources above.
Questions about Suki
How does an AI scribe work?
An AI scribe typically works in four steps:
- Capture: a phone, computer or room microphone records the consultation after the patient is informed or consents.
- Transcription: speech recognition converts audio to text and separates speakers.
- Summarization: a language model extracts relevant content and drafts a note in the chosen format, such as a SOAP note, sometimes with codes or orders suggested.
- Review: the clinician edits and signs the draft, which is then filed in the EHR, often through an integration.
Each step can introduce errors, so final responsibility for the note stays with the clinician. Ask vendors whether audio is stored, whether data is used to train models, and how fabricated or missing content is measured.
What is “hallucination” in generative AI tools used in healthcare?
Hallucination is when a generative AI tool produces content that sounds plausible but is false or unsupported by its inputs, such as a symptom, medication or exam finding that was never mentioned in a consultation.
It matters most in documentation, summarization and question-answering tools, because errors can be copied into the medical record. Common safeguards are:
- Clinician review and sign-off of every generated note or summary.
- Links from generated text back to the source audio or record.
- Vendor testing that measures omission and fabrication rates in realistic conditions.
- Clear policies on what the tool must not be used for.
WHO's guidance on large multi-modal models highlights inaccurate or false outputs as a key risk.
What is AI medical transcription?
AI medical transcription automatically turns recorded clinical audio, such as dictations or consultations, into written text, sometimes followed by human editing (a hybrid model) before the document is returned.
It differs from real-time speech recognition mainly in workflow: transcription is usually asynchronous, working on audio files after the event, while speech recognition displays text as the clinician speaks. Some services combine automatic transcription with professional medical editors for quality control.
When comparing services, check turnaround time, accuracy measurement method, how corrections are handled, supported specialties and languages, where audio is stored and for how long, and whether the provider will sign the data processing agreements your jurisdiction requires.