Launching today
ClinicFrame
Like Granola, but for healthcare. Fully HIPAA-compliant.
158 followers
Like Granola, but for healthcare. Fully HIPAA-compliant.
158 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
@aswanth_viswanathan8
That's the right thing to ask for, and it isn't a count. Trust doesn't arrive after N notes. It arrives the first time the note contains something you would have forgotten to write down. For most people that happens in the first few visits, not after fifty.
What the first week actually looks like: onboarding runs a demo visit, so your first note comes out before you ever use it on a patient. After that the useful pattern is two or three visits a day, reviewing each note the same day instead of batching a week of them. You want to find the format you disagree with early, because your templates are what make the rest of the month cheap.
And I want the same thing you're asking for, so: anyone using it daily, how long did it take you?
Adomate
Hey Clemente, this looks really cool, congrats on the launch 🚀
You mention that it’s EHR-ready. Are you initially focusing on specific countries and healthcare systems, or is ClinicFrame designed to be international from day one? Healthcare regulations and EHR ecosystems vary so much between countries, so I’m curious how you’re approaching that.
Best of luck today!
ClinicFrame
@lucas_desard
Thanks. US first, and deliberately so.
Compliance doesn't generalize. HIPAA with a BAA is a specific regime, and PIPEDA or GDPR are not the same work with a different label on it. Doing two jurisdictions halfway is worse than doing one properly, especially when what you're selling is trust.
On EHR-ready it's worth separating two layers. Getting the note into a chart is the universal part: structured text in the format the record expects, which works in any system in any country. Direct integrations are the part that goes system by system, and those we do one at a time, starting with what our users are actually on.
Canada is the request we hear most after the US, so PIPEDA is the next jurisdiction we look at rather than a hypothetical one.
the shadow-IT framing is the strongest part here tbh, you're not selling a new habit, just a compliant version of one clinicians already formed on their own. the thing I'd want to know is edit friction, since the clinician signs the note and carries the liability, so time-to-correct probably matters more than aggregate accuracy.
ClinicFrame
@alex_watson2110
Right, the habit was already there. The only thing we change is where the data goes.
On edit friction, agreed, and the reason is that finding the error costs more than fixing it. Correcting two words takes seconds. Reading the whole note to be sure there's nothing to correct is the real tax, and that's the one nobody measures.
So what we watch is time from opening the note to accepting it, and how much of that time is reading versus typing. A note that needs no edits but three reads to trust is worse than one where you fix a word and move on. Tracing each line back to the audio exists for exactly that: you check the one line you doubt instead of re-reading the encounter.
@clemente_lopez1 the read-versus-type split is a smart thing to be watching. one blind spot in it though: a fast accept is ambiguous. it is either trust you earned or someone not really reading, and both look identical in that metric.
the tell would be whether the notes accepted fastest are the ones amended later. if they are, that is complacency showing up rather than accuracy. line-level traceback back to the audio is the right fix for it either way, since it makes spot-checking cheap enough that people actually do it.
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.
Fuzzy AI
super needed!!! how do you find yourself different to fireflies?
ClinicFrame
@serenalam
Thanks. Fireflies is built for meetings, we're built for visits, and that changes almost everything downstream.
Three concrete ones. Nothing joins your call as a third participant, which matters because plenty of visits happen in a room, and a bot sitting in a therapy session is a non starter. The output isn't a summary with action items, it's a structured clinical note in the format your EHR and your payer expect. And the unit of memory is the patient over time, not the meeting.
Compliance is the floor: a BAA comes with the account at self-serve price, not as an enterprise add-on.
I spend a lot of time looking at AI applications in regulated industries, and most of them die in the gap between the demo and the compliance review. Starting from compliance and working toward the delight is the harder order to do it in, and the one that survives.
Congrats to the team. Rooting for this one.
ClinicFrame
@jesus_charinga_gutierrez
Thanks. That gap is real, and the reason the order matters is that compliance can't be retrofitted. You can add polish to a compliant product. You can't add a BAA to a data path that was built without one.
The question that kills those demos is never about the model. It's where the data sits and who signs for it.
ClinicFrame
There are plenty of AI scribes out there. We know that! But after talking to hundreds of clinicians, we realized the real challenge isn't just generating notes. It's building something they can actually rely on every single day.
We focused on what matters most: reliability, responsive support, and compliance. No dropped sessions. No unexpected downtime. Just a product that works when clinicians need it most.
We listened closely to our users and built the product they kept asking for.
This launch is much more than an AI scribe for us, it's the first step toward a broader vision of medical intelligence that helps clinicians before, during, and after every patient encounter.
Excited to finally share the work of so many months with the world. Thanks everyone for the incredible support here on Product Hunt. We can't wait to keep building with your feedback!