Reasoning · Inquiry · Tactical · Assistant

AI shouldn’t have to guess
what the evidence says.

RITA reads the whole record and turns it into a RITAPod™: a cited, de-identified, tamper-evident file that drops into whatever AI your firm already uses. Don’t take our word for it. Download a finished case, drop it in, and check every citation yourself. Then try to make it guess: ask about a visit that isn’t there, a diagnosis nobody made, a date that never happened. It will tell you it isn’t in the record.

Synthetic caseRachel Sutton is a fictional patient. Real medical-legal workflow, no PHI, nothing to sign.
Download the Sutton RITAPod™ (.zip) Request a Demo or look at the sample reports →

Works in the assistant your firm already runs: a general chat assistant, your case-management AI, or a private model. Nothing to install — the GUIDE is inside the zip.

Don’t compete with the AI. Supply the AI.
1 · RITA

Reads the record.

Every page, on our hardware, never a public cloud. Builds the chronology, checks the billing, finds the traps, and refuses to guess.

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2 · RITAPod™

Makes it portable.

One file, two forms: JSON for chat assistants, a PDF twin for case systems. Cited to the page, identifiers removed, a hash on page one so nobody can quietly edit it.

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3 · A person signs

Reviewed before it ships.

A credentialed professional checks the pod and puts their name on it. Software doesn’t vouch for medical facts; people do.

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4 · Any AI

Reads it better.

Drop it into the assistant your firm already runs. The better their models get, the more the pod is worth. We test that in public, and we don’t name the readers.

Patent Pending

Introducing RITAPod™

Prepare the evidence once. Reason with it anywhere. A portable, de-identified version of a case that drops into any AI assistant your firm already uses — on a laptop, a monitor, or your phone. RITAPod™ lets the next AI reason over the chart without reconstructing it. Ask it anything, out loud or typed, the second you need it.

  • The file stays put — RITA and your raw records stay on hardware nobody else shares; only the de-identified packet ever leaves
  • Portable — the case travels with you, no login required
  • De-Identified, Second-Checked — every packet is scrubbed and independently re-verified before export; if the check doesn't clear, it doesn't ship
  • Citation-Grounded — every answer traces back to the record
  • Four Lenses — Plaintiff, Defense, Expert Prep, Neutral, one pod

13 clinical events · 3 episodes · 6 facilities · identifiers scrubbed and machine-verified · synthetic demo case, not a real patient.

How to use it
  1. Unzip it. Open START-HERE.txt if you want the two-minute version.
  2. Drop DropMeInYourFavoriteAI.json into the assistant your firm already runs — a general chat assistant or a private model — or DropMeInYourCaseSystem.pdf into your case-management AI. On your phone, use voice mode and just ask.
  3. Ask a question, then open the PDF to the page it cites. If it can’t cite it, it tells you.
Try to break it
  • Ask for a case summary, then open the PDF to every page it cites.
  • Ask about a visit that isn’t in the record. She should tell you it isn’t there.
  • Ask her to confirm a diagnosis nobody made, or a date that never happened.
  • Ask what the defense would use against this case — then check that every point traces to a page.

If you can make her guess, send me the transcript: [email protected]

Three cases on this site

Sutton is the 40-page demo above: download it and try to make her guess. Okafor is the 1,000-page exam in the Test Log, built to break her, with every miss published. Jordan Avery is the case behind the twelve sample reports. All three are fictional patients.

The case
travels
with you
The RITA Test Log

Does the pod make the reader not matter?

Most AI in legal tells you an accuracy number. Almost none of it shows you the test. Every few weeks we publish a record built to fail the way real records fail, the answer key, what RITA got wrong, what she refused to ship, and what happened after we fixed it. Run it on anything you like.

3 → 12 / 13
the AI reader that cannot hold a 1,000-page file, raw record → verified pod
10 → 12 / 13
the two strong readers, raw record → verified pod, zero inventions
13 / 13
answers on which all three readers agree from the pod
4
exports refused by independent verification before one shipped

Issue 2, “Ramirez-Holt”: a 1,000-page record RITA had never seen, thirteen preregistered questions, three AI readers by kind, five exports before one passed, every failure published. Issue 1, “Okafor”: 1,000 pages, 18 traps, six runs, every miss published. Next: 2,500 pages.

Same Case · Same Questions · Same AI

What changed was the file, not the model.

We took the 1,000-page Okafor record from the Test Log and gave it to a widely used case-management platform’s built-in AI twice: once as the raw record, once with the RITAPod™ in the file. Same assistant, same day, same questions an attorney would ask. Here is what it volunteered each time.

AskedRaw recordWith the RITAPod™
What are the medical specials?Reported $44,696 as a “floor.” No mention that any of it was duplicated.$44,696 printed, $44,396 corrected. Flagged the total as provisional until the billing check passes and pointed to the $300 duplicated on 04/01/2026 at OKAFOR-000786.
Anything wrong with the production?Nothing volunteered. When asked directly whether the patient ever had a knee replacement, it found the page.Led with it. Page OKAFOR-000737 belongs to a different patient and was excluded from the chronology, stated in the first answer.
What will the defense use?Good general weaknesses. Never surfaced the 2022 note documenting neck symptoms before the collision.Cited the 2022 note as the pre-existing-condition fight, with the page, alongside the later “denies neck pain” visits that answer it.

The fair reading: the assistant is a good reader. Asked directly, it found two of the three on the raw record. With the pod it told the attorney before anyone knew to ask. The raw read also found two things our pod didn’t carry, an outcome score and a billing line with no itemization; both are in the pod now. That is the loop: every reader we test teaches the file something. Readers are described by kind, never named or ranked. Full method and downloads on the Test Log →

What She Produces

Twelve reports from one record. Here are two.

From merit screen to expert rebuttal, RITA generates the full litigation suite from a single case file, every finding cited to its page. These two show the same banner reaching opposite verdicts: one report failed its own quality check and says so; one passed and says that just as plainly. Hover the dots.

Merit Screen QA banner
This report failed its own QA check — and says so, right in the deliverable, instead of quietly shipping a shaky number.
She names exactly which upstream data made this report provisional — the charge ledger and the billing check that failed — not a vague "needs review."
Flag a problem, then hand you the one-click path back to source — not just a warning with nowhere to go.

Merit Screen — Fails Loudly, Not Quietly

When the underlying data is provisional, the report is marked "QA Fail — Provisional" instead of presenting it as settled fact.

View full report →
Treatment Timeline QA verified banner
The intake facts sit right above the QA verdict — so you can see exactly what was checked before RITA calls it clean.
Not every report gets flagged. When the record checks out clean, RITA says that too — the same banner, the opposite verdict.
A clean QA verdict doesn't mean the analysis stops — she still builds out the full litigation timeline underneath it.

Treatment Timeline — Verified Clean

The honesty cuts both ways: this one passed every QA check, and the report says so just as plainly.

View full report →

Every sample is a real RITA-generated report from the Jordan Avery case, a synthetic record built to be shown, not staged.

Local & Secure By Design

Your file never touches a public cloud.

Managing partners and defense counsel don't need another vendor promise about HIPAA — they need an architecture that makes the question irrelevant. When a patient file comes in, it's processed entirely locally, no public cloud AI service ever sees it.

Processed Locally, Not in the Cloud

The moment a patient file arrives, it's read and reasoned through entirely on local infrastructure — never uploaded to a public cloud AI service for analysis.

PHI Never Exposed

Because processing never leaves local infrastructure, protected health information is never exposed to a third-party cloud environment — in transit or at rest.

No Public AI, No Data Sharing

Your case is never sent to a shared or third-party AI model. The reasoning happens in one controlled, local process, start to finish.

The one deliberate exception: a certified, de-identified packet — a RITAPod™ — may leave to run inside an AI assistant your firm already uses. The raw file never does.

Today

We run RITA for you.

Send the records and we process them on our own workstation, in our own building, with no public cloud AI in the path. Sutton-size records come back next day; larger records are quoted per case, and the machine times are on the Test Log. You get the reports and the RITAPod™; the raw file is purged on request.

Later this year

RITA installs in yours.

A dedicated appliance inside your firm’s own network, behind your firewall, so records never leave the building, not even to reach us. Updates arrive over a brief connection or fully offline by USB, your choice.

Who RITA Works For

She does the reading. Your team still does the deciding.

RITA isn't here to replace the paralegals and legal nurse consultants who already know these cases cold. She's here to hand them a fully-cited first pass — record read, timeline built, findings sourced back to the page — so the person who signs their name to the work spends their time reviewing and judging, not scanning 1,400 pages of records to find the one line that matters.

Faster First Drafts

Hours of chart review compressed to minutes, not replaced.

You Stay the Decision-Maker

Every finding is a citation you can check, not a verdict.

More Cases, Same Team

Capacity to take on more work without burning out the people doing it.

About Us

A Note From Our Founder

I didn't set out to build a piece of software. I set out to build something that could serve the people doing this work — the way my father meant it when he used that word with me.

He wasn't talking about business. He was talking about a way of showing up for people... doing the work not to be faster, or flashier, or first, but because it actually helps someone. When he said it, something clicked. That's what RITA is supposed to be. Not a replacement for the paralegals and legal nurse consultants and attorneys who've spent years learning to read a chart the right way — an extension of them, built with the same care I'd want if it were my own name on the line.

I've come to understand something while building this: whatever you build reflects who you are. Your morals, your standards, what you're willing to let slide and what you're not. So I've tried to build RITA the way I'd want to be treated — honestly, plainly, never pretending to know something she doesn't.

RITA will never be perfect. I will never tell you she is. Every record is different, every case has something she hasn't seen before, and there will always need to be a person in the loop to catch what she misses and decide what matters. That's not a flaw we're patching around — it's the whole design. She's meant to keep learning alongside the people who use her, the same way any of us do.

Search how other medical-legal companies describe themselves and you'll find faster, smarter, cutting-edge. You won't find serve. I want that to be the word people remember about RITA — not that she's perfect, but that she was built to actually help, and to respect the license of everyone who trusts her with their case.

— Peter, Founder

Run one of your real cases through RITA

Send the records. Sutton-size files come back next day, larger ones are quoted per case, and every page is processed on our hardware and never on a public cloud. See exactly what she does on a case that matters to you.

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