Trained, not adapted
We build models on legal text from the start rather than bending a general-purpose model toward the domain. The training data is the difference, and we do not compromise on it.
Company
A research company with one subject.
BRELYNE develops foundational AI models for the legal domain, and nothing else. The focus is the whole strategy. It lets us train on legal text, measure against legal work, and hold every model to a single standard rather than a general one.
The thesis
We treat law as the discipline it is.
Our aim is to make legal AI more effective, more efficient, and more scalable, and to set the benchmark for accuracy and efficiency in the field. We do that by refusing the shortcut. General-purpose models can read a contract, but they were never built to be right about it, and in legal work being nearly right is often the same as being wrong.
Everything we build begins with problems we have lived in legal practice and legal technology, from extracting a single date buried in a contract to surfacing the one decisive citation hidden across thousands of cases. Those are not hypotheticals. They are the reason the company exists and the measure we hold every model to.
How we work
Four commitments
These are the principles the model family is built on. They are also how we decide what to build next.
Measured against practice
Every model is held to the accuracy the work demands and benchmarked against the alternatives. Our retrieval models rank among the top performers on independent legal benchmarks.
Structure over summary
We render law as connected structure you can traverse and verify, not a paragraph that hides its own reasoning. A result should be something you can follow, clause to citation.
Confidential by design
Legal data is privileged. Our deployment options, down to air-gapped containers, exist so capability never costs you confidentiality.
Who we build for
The people who do the work
We build for legal-technology companies and the law firms they serve: the teams responsible for finding the controlling authority, reading the contract correctly, and standing behind the answer. The models are meant to sit inside their products and their workflows, not replace the judgment that surrounds them.
That audience keeps us honest. It is a group that can tell the difference between a result that looks right and one that is right, which is exactly the standard we want to be held to.
Focus
Foundational AI for the legal domain. Retrieval, enrichment, and the infrastructure beneath both.
Built for
Legal-technology companies and the law firms they serve.
Standard
Benchmark-leading accuracy and efficiency, measured on independent legal retrieval and embedding benchmarks.
Reach
Hosted platform, cloud marketplace, or self-hosted and air-gapped, with one identical API.
On the horizon
The corpus and the models, together.
Next comes a proprietary repository of laws, decisions, and contracts from around the world, graphitized and ready for the models to reason over. Built for each other, so retrieval and structure arrive with the corpus rather than after it.