Criterica Intelligence — 23,706 production models trained on 475M+ real court records
Bespoke Data Science

Your book. Your models. Your expected outcomes.

Criterica trains bespoke outcome models on a client's own portfolio, blended with the 475M+ record base and 23,706 production models, so expected outcomes are tuned to the exact book being priced, funded, insured, or managed.

"A general model tells you what tends to happen. A model trained on your book tells you what tends to happen to you. The base supplies breadth no single portfolio can hold. Your data supplies the signal only your portfolio carries. The work is fitting one to the other without ever taking the raw data out of your hands."

Their data plus the base

Trained on the portfolio you actually hold.

Every bespoke model starts from your proprietary portfolio — your matters, your counterparties, your venues, your realized outcomes. That book carries signal no external dataset can reconstruct. Trained alone, it is too narrow to generalize.

Blended with the Criterica base of 475M+ real court records and 23,706 production models, the narrow signal gains the breadth to hold up out of sample. Your data plus the base beats either alone. The result is a model whose expected outcomes are tuned to the exact book being priced, funded, insured, or managed.

Clean Room & Federated Training

We never hold your raw data.

Institutional buyers do not get to hand over raw loan-level or claim-level data, and they should not have to. Models can be trained inside your own environment, or inside a secure clean room where only derived features move and the raw records never leave your control. Criterica trains against the signal without ever taking custody of the book.

Data control is the single constraint that blocks banks, insurers, and large funders from working with an outside modeling partner. Remove the constraint and the engagement is unblocked. The clean room is not a compliance checkbox bolted on at the end. It is the architecture the whole engagement is built on.

YOUR ENVIRONMENT
Raw records stay here
CLEAN ROOM
Derived features only
CRITERICA BASE
475M+ records · 23,706 models
PRIVATE MODEL
Tuned to your book
Raw loan-level and claim-level data never crosses the boundary. Criterica trains on features, not the book.
475M+
Base records
real court records
23,706
Production models
validated outcome models
28,212
Total models
registry entries
16,302
Verified judges
judicial coverage
89
Jurisdictions
US, Canada, AU, UK
Engagement Models
01
Bespoke Portfolio Training
Funders, lenders, insurers, enterprise legal

Train an outcome model on your own proprietary portfolio, blended with the Criterica base of 475M+ real court records and 23,706 production models. Your data carries the signal specific to your book. The base carries the breadth no single book can hold. Their data plus the base beats either alone.

02
Clean Room & Federated Training
Banks, carriers, large institutional funders

You do not have to hand over raw loan-level or claim-level data. Models train inside your environment, or inside a secure clean room where Criterica never holds the raw records. Data control is the constraint that blocks most institutions from outside modeling. Removing it is what unblocks the engagement.

03
Private Model Hosting
Recurring-use clients, platform partners

Client-only models hosted under defined SLAs, with explicit versioning and a fixed refresh cadence. Every prediction is traceable to a model version. Every version is retrained on a schedule you set, against data that stays under your control.

04
Validation & Challenger Models
Model-risk teams, regulated lenders and insurers

Audit the auditor. Independent validation and challenger-model benchmarking of your existing internal models: how often each is right, how well it separates strong cases from weak, and how stable it stays, measured against a jurisdiction-matched base. Built to support model-risk-management mandates, not replace your governance.

05
Embedded & White-Label
Software platforms, data providers, marketplaces

Outcome models a partner platform can ship under its own brand, powered by Criterica underneath. Your interface, your customer relationship, our validated data science. Delivered as a private model surface, not a logo on a slide.

Engagement Process

Six steps from your book to a private, tuned model.

The raw data never leaves your control. The model never leaves the version trail.

01
Scope

Define the decision the model serves — pricing, funding, reserving, or portfolio management. Identify the target, the population, and the constraint set before any data moves.

02
Data clean room

Stand up a secure clean room, or connect inside your environment. Raw loan-level and claim-level data stays under your control. Criterica works against features, never the raw book.

03
Train

Train on your portfolio blended with the Criterica base, against real court data, never synthetic, with checks that keep the model from ever seeing the answer in advance.

04
Validate

We document how often it is right, test it on cases it never saw, and check it against what actually happened in comparable matters. The model ships with its reliability shown, not asserted.

05
Deploy

Private hosting under SLA. Client-only access, explicit versioning, every prediction traceable to a sealed model version.

06
Refresh

Quarterly retrain against new outcomes and an expanding base. Reliability is re-measured each cycle so the model stays tuned to the book as it changes.

Commission a model.
Tell us about your book. We design the data science.