Launching today
ClinicFrame
Like Granola, but for healthcare. Fully HIPAA-compliant.
99 followers
Like Granola, but for healthcare. Fully HIPAA-compliant.
99 followers
An ambient AI scribe that writes clinical notes in real time so you can focus on your patient. It passively captures every visit, whether in person or virtual, and delivers a complete, structured clinical note the moment the encounter ends. HIPAA compliant, desktop native, and EHR ready in seconds. We're launching Scribe today, with a much bigger vision ahead: a medical intelligence platform that goes beyond documentation to support the entire clinical workflow.
ClinicFrame
Hi Product Hunt 👋 Clemente here, I lead ClinicFrame.
Three years ago we launched CompliantChatGPT, a HIPAA-compliant AI assistant for clinicians. More than 8,000 have used it since: therapists, psychologists, oncologists, nurses running home visits. They weren't shopping for AI. They came because they were already putting patient information into a consumer chatbot, with no BAA, no audit trail, and no answer for the surveyor who asks where that data went.
After three years of listening to them, the pattern was hard to miss. Almost every conversation ended up at the same place: the note. And most clinicians were writing each one twice, first as scribbles during the visit, then properly, hours later. Notes were never the job. So we built the tool that writes them.
🩺 What ClinicFrame Scribe does
It listens to the visit, in person or virtual, and writes the structured clinical note as it happens. Desktop native, so nothing joins your call as a third participant. SOAP by default, your own templates on top. You review it, you sign it, you stay the author, and it lands in your EHR in seconds.
🔒 HIPAA compliance is the floor, not the upsell.
A BAA comes with the account at self-serve price. Documenting a visit safely shouldn't require a procurement cycle and an enterprise contract, which is exactly what the big model providers ask for today.
🧭 Today it's a scribe. That's the starting point, not the plan.
We're building the operating system for a clinical practice: the context of every patient, the record of every visit, and the part nobody volunteers for, dealing with insurers. The note is where that starts, because the note is where the billing code comes from. Revenue is what we build next, with the clinician reviewing every code before anything leaves the building.
Most software in a clinic was built for the billing department and handed to the clinician afterwards. We're building it the other way around.
🧱 Every Ai medical tool on the market started as a scribe. We started three years earlier, on the compliance side, with 8,000 clinicians running real clinical work through a product that had to hold up to a BAA from day one. That's the harder half of the problem, and it's already done.
👥 Who it's for: clinicians who document their own visits. Therapists, private practices, home health agencies, small clinics.
🎁 For the PH community: 50% off for 3 months, on top of the 7-day free trial. No card to start, and onboarding runs a demo visit so you get your first note without waiting for a real patient.
🙏 Our ask: if you document patient visits, what's the one thing you'd never let a tool do with a session? That's the answer I care about most. I'll be in the comments all day.
@chiara_tucci @macarena_balparda @alan_brande are here with me today, and thanks to @mishaal_rashid and @francesco_domizio for the hunt.
to answer the question you actually asked - pick a billing code on its own. everything else in the note is a record of what happened, but the code is a claim submitted to a payer, and the liability for it sits with the clinician, not the tool. you mention the clinician reviews every code before it leaves the building, which is the right instinct, but I'd push on how that review is presented. if the suggested code is shown as "the note says X, therefore code Y" it's very easy to rubber-stamp under time pressure, same failure mode as any confident-sounding suggestion. does the review step force the clinician to see the specific line in the note the code was derived from, or just approve the code itself
ClinicFrame
@galdayan
Right, the code is a different object. The note records what happened. The claim asserts it to a payer, and the clinician signs for it.
So the code never appears on its own. It appears with the exact line in the note it came from, and with whatever is still missing for it to hold. You approve the evidence, not the suggestion.
And when the visit doesn't support a code cleanly, we don't offer one. We say what's missing. Fewer suggestions, each one traceable, is the only version of this that survives an audit.
And after that comes the part where the insurance company denies the claim and we have to file an appeal—and here’s the real magic of it all: if we have the context, the evidence, and the reasons, we can automatically generate the appeal letter for the insurance company.
And of course, everything related to RCM—collecting a percentage of the transaction amount.
I'm not in healthcare, but the idea really got me. Really, congrats on the execution. The line about clinicians writing every note twice gets to the real problem. The transcription is useful, but cutting out that second round of admin is where the value is. I’d be interested in how ClinicFrame handles situations where the conversation is incomplete, contradictory, or clinically sensitive. Does it clearly flag uncertainty and missing details, or can a polished note make the output look more certain than the visit actually was? Keeping the clinician as the author is the right approach. The review step needs to be genuinely quick without encouraging people to skim.
ClinicFrame
@os_ishmael
Hey! Thanks for your comment, and you're absolutely right!
1. We point out any parts that weren’t fully understood to avoid errors.
2. Those comments can be edited, both in the transcript and directly in the note.
3. Once everything is ready, it’s ready to be exported and sent.
The interesting thing is that we’ve seen the quality of the product and the transcription, which allows us to guarantee 96% accuracy, so errors are minimal these days.
Ambient audio capture of clinical encounters is genuinely useful but it's also the highest-stakes category for AI hallucination, a fabricated medication dosage or an incorrectly captured allergy in a clinical note is a patient safety issue, not just a bad output. What's the accuracy validation methodology for ClinicFrame's notes, like how are you measuring and communicating accuracy to clinicians who are relying on these notes for clinical decisions?
ClinicFrame
@ansari_adin
You're separating the right things. A missed nuance in the narrative and a fabricated dosage are not the same class of error, and reporting one accuracy number is how that second one stays hidden.
So we don't track a single score. We look at error rates by content class, and we count omissions and fabrications separately, because they have opposite fixes. For the high-risk classes (medication, dose, allergies, any number) the rule is that nothing enters the note unless it was said in the encounter. The model doesn't complete from prior knowledge, and anything unclear is marked as missing rather than filled in.
The second half of your question matters more than the first. Every line traces back to the audio it came from, so review takes seconds instead of a full re-read, and the note stays a draft until the clinician signs it. Accuracy a clinician can't inspect isn't accuracy, it's a claim.
If you've done validation work in this space, I'd want that conversation.
@Granola is known for being sneaky since it doesn't inform participants on the call that it's recording. Does ClinicFrame alert the patients before they are recorded?
ClinicFrame
@himani_sah1
This is a very important question.
By law, the patient must ALWAYS be asked for prior consent before recording the session, and it is the doctor’s responsibility to do so.
In our app, the doctor must also confirm that they have obtained prior consent before starting to record.
Not in healthcare myself, but I have watched this team work and the discipline is the thing. Narrow problem, real users, no attempt to be everything at once. Congrats on shipping. Curious how you think about expanding beyond the note itself once clinicians trust the workflow
ClinicFrame
@artstavenka1
Thanks. The expansion follows the note, it doesn't leave it.
Trust gets earned in order. First the note has to be good enough that you stop editing it. Then the patient context between visits, because the note already holds it and rebuilding that history by hand is the next tax after documentation. Then the revenue side, because the billing code comes out of that same note.
Each step is only allowed by the one before it. We don't get to touch a claim until the note is boring and reliable.
Congrats on the launch, Clemente! The framing here is what makes it click for me — starting on the compliance side three years ago and arriving at the scribe from the clinician's side rather than the billing department's. That's the opposite of how most of these tools are built, and it shows.
To your question — the one thing I'd never let a tool do unsupervised: close the loop between the note and the claim without the clinician seeing exactly which line justified the code. Gal's point above is the whole game. A scribe that writes a beautiful note is table stakes; the trust breaks the moment a suggested billing code gets rubber-stamped under time pressure. If ClinicFrame makes the clinician confront the specific sentence the code came from — not just "approve Y" — you're building something structurally safer than anything that treats the code as an afterthought.
Rooting for you. The "compliance is the floor, not the upsell" line should be on a billboard.
ClinicFrame
@camilo_mera
Thanks, and you drew the line exactly where we drew it. The clinician signs the claim, so the clinician has to see what it was built on. Anything else moves the liability onto the person with the least visibility.
Your read on the note is right too. Writing a good note is the entry ticket. What happens to that note afterwards is the actual product.
If you end up trying it, tell me where it annoys you. That's the feedback I act on fastest.
And I'll take the billboard.