Two sectors live on recorded conversations and can almost never use an off-the-shelf AI tool: healthcare and law firms. A consultation, a note, a statement, a client meeting. In both, the content is about as sensitive as it gets, and in both you need to be able to trace exactly what was said — not a tidy summary nobody stands behind.
Run-of-the-mill AI transcription has a double problem here. First, it sends your audio to a US cloud that, often, uses it to train its models: a clinical recording or a client matter can't go out that door. Second, it hands you flat text you can't check: if the model makes a sentence up, you have no way to go back to the audio and see it. For notes from an internal meeting, fine; for a medical record or a case file, not.
Privacy isn't a marketing promise, it's where the service runs.
And the report can be verified. Instead of a summary you have to trust, every relevant claim is anchored to three things: the literal quote, who said it, and the exact minute. We call it the evidence graph, and it marks the status of each point: what was said verbatim, what is conditional, what remained disputed —two conflicting versions, without the system picking one for you— and what is inferred. The PDF ships signed, so a third party can check nothing was altered without trusting us. You can see a real one here: sample report (signed PDF).
Where it pays off most is the «disputed» status. When two parties in a recording don't agree, the report keeps both versions anchored to their quotes instead of flattening them into one sentence: exactly what you need for minutes, a record of commitments, or the summary of a recorded statement. Each point keeps its minute, so you can go to the audio and hear it. And the signed PDF gives you a checkable trail of the document, not a Word file anyone can rewrite.
A consultation or a dictation becomes transcription + summary + detected entities —medication, dosages, dates, people—, with each datum anchored to what was said. The clinician sees where every point comes from and validates what matters, instead of replaying the whole recording. And the patient's audio doesn't go to a third party nor sits stored anywhere.
In the report's own words:
«It is not a certified or sworn transcript, and the client must validate it before using it for any action or decision with consequences.»
Specifically: it is not a certified medical record, nor a medical device, nor a sworn transcript, nor legal or medical advice. The graph proves something was said and that the document is authentic; it doesn't prove what was said is true. And the legality of the recording —the consent of whoever is speaking— is the responsibility of whoever provides it, not ours. The professional is still the one who decides; the tool just lets them see and check the material faster.
If your firm or clinic works with recordings and this fits, you can try it today —the API is OpenAI-compatible, it drops into what you already use— and write to us to discuss a formal data-processing agreement. How to request the report, in the verifiable-report documentation.
Anything to add or correct? Write to support@uttera.ai. If you correct us, we edit the post and credit you.
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