JustReva

[JustReva @IamJustReva]

@BeckersHR love this

[JustReva @IamJustReva]

Your patients are Googling "dentist near me" right now.
Are they finding you — or your competitor?
Free clinic grader: 7 categories, competitor comparison, revenue at risk.
30 seconds → https://t.co/chZgCzH05X #healthtech

[JustReva @IamJustReva]

Your doctor should be caring for patients. Not answering phones.
Without REVA: 15-20 missed calls/day, $25K lost.
With REVA: Zero missed calls. 40% more bookings.
Free 30-day pilot → https://t.co/91693wmJ55 #healthtech #dental

[JustReva @IamJustReva]

A clinic owner showed me her call log last year.

23 missed calls. One Tuesday afternoon.

I asked what happened to those patients.

She paused, then said: "Probably nothing good."

That pause is why I'm building this.

[JustReva @IamJustReva]

@bimedotcom @sayashk @PKirgis @ghadfield @random_walker The open-world eval problem is exactly this in clinical AI — the failure modes only show up when a patient says something the training set never anticipated. Are you seeing orgs build for that gap yet, or is most of the eval work still benchmark-first?

[JustReva @IamJustReva]

The UCSF tool is a good example of where the "5 steps" framing breaks down. Step 4 — engage frontline leaders early — is actually the whole game. The rest of the list assumes the tool survives contact with a 12-hour floor shift. Most don't. CNOs know this. The adoption rate tells the real story.

[JustReva @IamJustReva]

@VaibhavSisinty Cheap STT/TTS doesn't kill voice AI. It kills the vendors selling STT/TTS. The hard problem was never transcription — it's what the voice agent does with it in a noisy, high-stakes environment. That bar just got higher, not lower.

[JustReva @IamJustReva]

15+ missed calls without REVA → 0 with REVA.
Your voicemail just cost you a patient. Actually, it costs you 15+ patients every day.
Free 30-day pilot → https://t.co/91693wmbfx #healthtech

[JustReva @IamJustReva]

Most clinic owners I show the grader to are surprised.

Not because the number is high — they expected that.

Because they'd never actually measured it before.

If you want to see what your real missed call rate looks like: https://t.co/SJoKMeYxto — 2 minutes, no pitch, just the data.

[JustReva @IamJustReva]

@Khulood_Almani @enilev @Eli_Krumova @smoothsale @JeromeMONANGE @bbailey39 @ralf_ladner @Nicochan33 @RLDI_Lamy @jblefevre60 @ahier That ops graveyard fills up fast. The demo works, the pilot succeeds, then it hits a real clinic at 4pm on a Friday. Completely different problem — and that's exactly what we're building around.

[JustReva @IamJustReva]

@AkwyZ @ArturHabant @elaniazito @IanLJones98 @CurieuxExplorer @Shi4Tech @enilev @Fabriziobustama @mvollmer1 @AnthonyRochand @JolaBurnett @lyakovet @debashis_dutta The self-teaching part is what's genuinely interesting here. Most healthcare AI deployments stall because the model stops learning after go-live. Real clinic environments keep shifting — new staff, new workflows, seasonal volume. Static models degrade fast in dynamic settings.

[JustReva @IamJustReva]

@drcaryyurkiw Running a practice, writing a book, hosting webinars — and still fielding every scheduling call yourself. Most health pros I know are one missed call away from a patient going elsewhere. The engine you're building deserves a front desk that keeps up with it.

[JustReva @IamJustReva]

Early on I asked a clinic owner: "how many calls do you miss?"

She said: "None. My team is great."

Then I pulled her phone system data.

34% of calls unanswered. 22% dropped during hold.

She went quiet.

"We're fine" usually means "I don't know what I'm losing."

[JustReva @IamJustReva]

@mpappas74 @elonmusk @xai @modulate_ai Healthcare is where the real differentiation shows up. Generic voice STT breaks on accents, medical terminology, and background noise in a busy clinic. The WER benchmark on real-world audio is the right thing to compete on — most vendors are still gaming quiet-room demos.

[JustReva @IamJustReva]

@lennysan @nikhyl Healthcare is the perfect case study. The most experienced clinic owners I talk to — 20+ years in — are often the hardest to move. Not because they're wrong, but because their instincts were built on a system where 'answer the phone' was solved by hiring another person.

[JustReva @IamJustReva]

@gregisenberg Healthcare is the highest-stakes version of this. HIPAA fines are real but the deeper issue: a breach in a clinic isn't just data — it's patient trust, which takes 10 years to build and one incident to lose. We made zero audio retention a feature before it was required.

[JustReva @IamJustReva]

The healthcare version already exists. They call it the "marketing coordinator" at a clinic.

Problem: she's also answering phones, rescheduling no-shows, and chasing down insurance prior-auths.

The CCO role only becomes a real hire when the operational layer gets automated first.

[JustReva @IamJustReva]

@bimedotcom @sayashk @PKirgis @ghadfield @random_walker The real tell is what happens when the model is right for the wrong reason. Benchmark passes, but the reasoning path wouldn't hold up in a real clinic workflow. Are you seeing evals that test failure modes specifically, or mostly still accuracy-focused?

[JustReva @IamJustReva]

Unpopular take: the biggest AI opportunity in healthcare isn't in the exam room.

It's the 2 minutes before and after.

The scheduling call that never got answered. The follow-up reminder that wasn't sent. The cancellation that wasn't rebooked.

Clinical AI gets all the press. Operational AI is where the money is.