[NAME_001], 52F · Visit [DATE_001]
PMH: HTN, T2DM. BP 142/88, A1c 7.8. Plan: discussed medication adjustment.
"Write a clean A&P note for this visit, focused on HTN and T2DM plan changes."
Maria Lopez · 52F
Jan 12, 2026
Assessment & Plan
- HTN: BP 142/88 — increase metformin to 1000mg BID
- T2DM: A1c 7.8% — RTC 3mo for repeat
A safer AI workspace for clinical documentation.
Patient data never leaves your side.
ScribeGo helps healthcare professionals de-identify medical records, organize complex clinical information, and generate high-quality documentation while keeping patient privacy at the center.
Runs on infrastructure clinics already trust
HIPAA compliant
from $0.
Every paid tier ships with our standard Business Associate Agreement. Click through, sign electronically, and start working with real patient data the same minute you create your account. No procurement, no sales call, no $30,000 minimum.
That isnt how most clinical AI tools price it. They gate the BAA behind their enterprise sales motion. We dont. The entire point of ScribeGo is to be the legal path between a clinician and a modern LLM, so we put it in every plan.
Most clinical AI tools treat HIPAA compliance as a premium feature you negotiate for. Thats a legacy of the old enterprise sales motion, useful when each BAA cost a thousand dollars to issue.
Our BAA template is already drafted. AWS BAA covers us upstream. The same tokenization pipeline runs on every tier. The marginal cost to sign one is zero, so we dont charge for it.
The Enterprise tier still gets a negotiated BAA with custom indemnification, breach SLAs, and data residency commitments. The click through is just the base layer.
Six steps. About a minute.
Every note runs through this pipeline. Patient info is hidden from the AI the entire time, then put back on your side.
Paste or upload
Drop in a transcript, fax, PDF, or photo — anything you would normally type up by hand.
Paste up to 100k characters of dictated text, or drag in an image / PDF. Nothing gets uploaded until you hit Generate.
OCR if it is a scan
Image and PDF text is extracted automatically before anything else runs.
AWS Textract reads fax printouts, photos of paper notes, and scanned PDFs into clean text. Skipped entirely if you pasted typed text.
Find patient info
Every name, date, MRN, SSN, dosage, and location gets located in the raw text.
Amazon Comprehend Medical plus our own matchers handle the detection. Double-click anything they miss to flag it yourself.
Tokenize before the AI sees it
Each PHI item is swapped for a placeholder like [NAME_001]. The model only sees the de-identified version.
The token map stays on your side. Patient info never leaves your AWS account, never reaches the LLM provider, never appears in logs.
AI writes the note
You pick the model and the template. Claude, GPT, or Nova drafts the clean clinical document.
SOAP, A&P, referral letter, prior auth, custom prompt — the LLM works with tokenized text and a template you control.
Names get put back, locally
Placeholders are swapped back with the original PHI on your side. Done in seconds.
Copy, edit, save to a project, or refine via chat. You can also export the de-identified version if you ever need it for research.
Try it. Takes about a minute.
Paste any clinical note. See what comes out. No signup needed.