Generic ASR hands back text. A healthcare product needs medical-grade recognition, a finished clinical note, and structured data it can write to a chart, all from one API.
General ASR is trained on podcasts and call-center audio, so it drops or invents clinical terms. Twofold's models are tuned on real visits and resolve medication names, dosages, lab values, and specialty vocabulary.
A transcript is raw text your product still has to turn into a note. Twofold returns a finished clinical note in the provider's voice, formatted to the template you request.
Instead of a wall of words, get typed fields you can write straight to your schema: the problem list, medications, billing-code candidates, and the fields your own templates expect.
Documentation only sticks if it fits the visit. One API covers ambient capture during the encounter, dictation, and upload after the fact, so adoption never depends on changing provider habits.
From raw clinical audio to EHR-ready output, build the documentation experience your product needs on a single healthcare speech-to-text and AI scribe API.
High-accuracy medical ASR with the clinical vocabulary and formatting generic transcription APIs miss.
Front-of-house dictation and post-visit summaries, structured the way clinicians expect.
Listens to the patient-provider conversation and drafts the note in the background.
SOAP, DAP, BIRP, GIRP, treatment plans, reports, and your own custom formats.
Problems, medications, ICD-10 and CPT candidates, and template fields, returned as typed data.
Outputs formatted to drop straight into your charting or downstream systems.
Tuned per specialty and per template: behavioral health, primary care, PT, and more.
Full voice-to-note and conversation-to-note pipelines, without stitching three vendors together.
Automate the documentation layer end to end. Providers review and sign instead of typing.
Send raw clinical input and get back a transcript, a finished clinical note, and structured, EHR-ready data, so your team builds the product experience instead of stitching together a documentation stack.
Medical ASR turns clinical audio, dictation, and multi-speaker conversations into an accurate transcript.
Clinical transcription APIThe transcript becomes a finished clinical note: SOAP, DAP, BIRP, treatment plan, or your custom format.
Medical note generation APIProblems, medications, ICD-10 and CPT candidates, and template fields are pulled out as typed data.
Structured clinical dataFormatted output writes straight into your EHR, or any downstream platform across billing, scheduling, telehealth, and more.
EHR documentation APIBook a call with our product team to walk through the documentation, talk through your use case, and find the implementation path that fits.
However your product reaches providers, Twofold's medical voice AI drops in behind it. Here's what teams build on each kind of platform.
Draft the note and write structured fields back to the patient record, so clinicians stop typing.
Surface ICD-10 and CPT candidates with the supporting note, so coders and claims start from structured data.
Turn intake calls and pre-visit conversations into structured summaries that pre-fill the chart and route to the right provider.
Capture the video visit and return a finished clinical note the moment the call ends, with nothing for providers to install.
Generate DAP, BIRP, GIRP, and treatment-plan notes from the session, tuned for behavioral health language.
Offer AI documentation as a built-in feature across every provider and specialty, managed inside your platform.
Give every clinician on your marketplace an instant AI scribe, so documentation stays consistent across the network.
Fire referrals, orders, and follow-up tasks from the structured data the visit produces, instead of parsing free text.
Add voice-to-note and structured capture to your app, so providers document by speaking on web or mobile.
A generic speech-to-text API hands back text. Building in-house means owning models, data, and compliance. Twofold gives you the whole medical documentation layer at a fraction of either.
| Twofold Medical voice AI the whole documentation layer | Alternative Generic STT API transcription only | DIY Build in-house your own ML stack | |
|---|---|---|---|
| Medical-tuned speech recognition | drug names, dosages, specialty terms | — general-purpose ASR | you train and maintain it |
| Returns a finished clinical note | SOAP, DAP, BIRP, custom | raw transcript only | Build it your own LLM layer |
| Structured clinical data extraction | problems, meds, ICD-10, CPT | Build it pipelines + eval | |
| EHR-ready output formatting | Build it | ||
| HIPAA-conscious, BAA available | — varies by vendor | Your scope compliance on you | |
| Built around provider workflows | ambient, dictation, upload | — you design each one | |
| Time to first integrated output | Days | Weeks plus your note layer | Months ML + data + eval |
| Cost at high volume | Lowest in-house voice AI | Per-minute adds up fast | Highest GPUs + ML headcount |
"Build it" means your team owns the models, prompts, evaluation, and clinical QA for that capability. A dash means partial or vendor-dependent support.
What developers, product leaders, and technical evaluators ask most about building on Twofold's medical voice AI.
A medical speech-to-text API turns clinical audio into text that is accurate for healthcare, then — in Twofold's case — into finished documentation:
Book a call with our product team to see the API and discuss your use case.
A generic speech-to-text API is built for podcasts and call-center audio and stops at the transcript. Twofold is a medical voice AI layer:
See the side-by-side in the comparison above.
An ambient AI scribe API listens to the patient-provider conversation and drafts the clinical note in the background — no dictation required:
Ambient scribing is one of several workflows — see the capabilities grid above.
Yes. Twofold is built for handling protected health information end to end:
Full details are in our privacy policy; our team will walk your security reviewer through specifics on a call.
Beyond the note, Twofold turns the conversation into typed, machine-readable clinical data your product can act on:
This is what lets you build coding, analytics, and EHR-write features on top of the voice layer.
We meet your product where it is — implementation is flexible rather than one-size-fits-all:
The fastest way to scope a path is to book a call with our product team.
Twofold runs its own voice and audio AI in-house instead of reselling third-party APIs, so the documentation layer costs less at scale:
Talk to our team for pricing against your expected volume.
Book a call with our product team to see the documentation, talk through your use case, and find the implementation path and pricing that fit your healthcare product.