Data & Platform Partners

The production model fleet is only as good as the corpus behind it, and the corpus is built from real court and regulatory records, not synthetic data, at production scale. Extending model coverage into a new jurisdiction, claim type, or regulatory domain depends on access to the records that describe how matters actually resolved there.

Criterica works directly with courts, government bodies, and legal-technology platforms that hold or generate that data, whether through public record access, structured data-sharing agreements, or platform-level integrations that make outcome data available at scale.

The relationship is reciprocal where it can be: a data partner gains access to the outcome intelligence the corpus supports, jurisdiction-level base rates, duration benchmarks, aggregate patterns, in exchange for the data access or integration that expands what the platform can cover.

This is the layer beneath everything else on this page. Every partner path described elsewhere on criterica.com ultimately depends on the corpus staying current, accurate, and broad, and that depends on the data relationships described here.

Coverage gaps are rarely permanent. They reflect where the corpus has not yet reached, and every new data relationship is a direct, traceable expansion of what the model fleet can responsibly cover.

Legal-technology platforms sit in a particular position here: many already hold structured, outcome-relevant data as a byproduct of the product they run, docket tracking, case management, e-filing, that was never built for model training but is often directly usable for it with the right governance in place.

Scopes what data access or integration would expand coverage in a specific jurisdiction or domain, and what governance and privacy terms that requires.

Builds structured ingestion for legal-technology platforms willing to make outcome-relevant data available at scale, rather than one-off manual transfers.

Shares aggregate, non-identifying intelligence back to data partners where that is useful to their own product or public mission.

Treats every data relationship as governed from the outset: what can be used, how, and under what public-records or contractual terms, agreed before any ingestion begins.

Works within whatever public-records access framework already governs a court or government body's data, rather than asking a public body to depart from its existing process.

Reviews a data sample against current model coverage before any broader agreement is discussed, where a platform is uncertain whether its data would be useful, so a platform knows concretely what its data would and would not add.

A description of the data held or generated: record types, jurisdiction and time coverage, and current access mechanisms, public, licensed, or proprietary.

Any governance, privacy, or public-records constraints that would shape a data-sharing agreement.

For legal-technology platforms specifically, a description of the current data schema and update cadence, which shapes how quickly a structured integration can be built.

Legal-technology platforms should also describe their own data-use terms with end users, since any integration needs to respect those terms rather than override them.

A description of any existing relationships the data has with other platforms or data buyers, so a new arrangement with Criterica is structured consistently with those existing commitments.

The first call scopes the data itself, confirms what governance terms apply, and identifies what a structured relationship, licensing, integration, or public-records access, would look like.

Where a public body is the counterparty, the conversation is scoped within whatever public-records framework already governs that data, rather than treated as a commercial negotiation from a blank slate.

Pilots typically begin with a bounded dataset, a single jurisdiction or a defined time window, so both sides can confirm data quality and format before a broader integration is built.

Once a pilot confirms data quality and fit, the relationship moves to whatever cadence, one-time transfer, recurring feed, or live integration, the underlying agreement calls for.