For life care planners, QMEs, and IMEs

Defensible medical chronologies for expert witnesses.

Built for work you'll be deposed on.

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The Bottleneck

The records keep growing. Your time doesn't.

A single case can come with thousands of pages of scanned medical records. Most practices outsource that review to offshore teams that take weeks, and errors still get through.

That review process is the bottleneck. It limits how many cases you can take, how fast you can turn them around, and how much time you spend on records instead of analysis.

What We Do

Eliminate the manual work.

We turn thousands of pages of medical records into a verbatim, cited chronology of medically important events. Every fact is extracted directly from the source record and linked to its page, so the chronology can be defended under cross-examination.

Why Us

Built for work you'll be deposed on.

Data Security

Built on HIPAA-compliant infrastructure. Your clients' records are never used to train AI models.

Built for Messy Data

We handle scanned PDFs, handwritten notes, and inconsistent formatting.

Built to the Expert Witness Standard

Expert witnesses stake their professional credibility on their reports. We built to that bar: verbatim extraction with AI quality checks. Not summaries.

About

Naomi Huang

Founder & CEO

Naomi is a machine learning scientist who spent six years at Uber and Stripe.

Caliber started when a life care planner friend asked her to solve a problem: he was turning away cases because record review was the bottleneck. The industry runs on offshore teams doing manual extraction — slow, expensive, and error-prone.

She built Caliber because she's spent her career shipping machine learning systems where mistakes cost millions of dollars. Expert witnesses put their name on the work and get deposed on it. They expect the same rigor.

Defensible medical chronologies for expert witnesses.

The records keep growing. Your time doesn't.

Eliminate the manual work.

Built for work you'll be deposed on.

Data Security

Built for Messy Data

Built to the Expert Witness Standard

Send us your first case.