Law firms · Courts · Compliance
Legal & compliance
Legal knowledge lives in millions of documents — cases, contracts, regulations — bound together by citations and cross-references. GreyCat turns them into one temporal knowledge graph with GraphRAG and a built-in MCP server, so your people and your AI agents get answers that are grounded, cited, and correct as-of any date.
Install GreyCat free Talk to us
The problem
Legal work is document work — but the answers live in the relationships between documents: which judgment cites which, which clause maps to which regulation, how a rule read on the date a contract was signed. Keyword search finds text and loses those links; a general LLM sounds confident and invents citations; and stitching a graph database, a vector index and a full-text engine together is brittle, and rarely point-in-time correct. Meanwhile the material is confidential, so shipping it to a third-party API is a non-starter.
How GreyCat solves it
GreyCat holds documents, the entities inside them and the citations between them as one graph, alongside vector embeddings and full-text search — so retrieval follows meaning and the network of authority. A built-in MCP server exposes it to AI agents directly, every value is versioned in time, and the whole thing runs as one self-hosted binary — no glue code, no data leaving your walls.
GraphRAG, not keyword search
Graph, vector and full-text retrieval in one query — find the relevant passage and the cases and clauses connected to it.
Citation & entity graph
Documents, parties, articles and precedents linked as they cite and reference each other — traverse the authority behind an answer.
Point-in-time correct
Every version kept — ask what a regulation or a contract said as-of any date, not just today.
Built-in MCP, self-hosted
Agents query the graph directly through the MCP server in the GreyCat binary — confidential material never leaves your infrastructure.
GraphRAG, grounded and cited
A question doesn't just match text — it lands on a node in a graph of authority. GreyCat retrieves the passage, then walks the citations and cross-references around it to assemble a grounded, cited answer.
Because every node and edge is versioned, the same question asked as-of a past date returns the law and the links exactly as they stood then.
Use cases
The same knowledge graph serves research, drafting and compliance — each answer traceable back to the documents and the links it came from.
Case-law & legal research
The problem. Finding the right precedent is more than matching words — you need the leading case and the network of judgments that cite it, and to know which are still good law.
Why GreyCat. GraphRAG retrieves by meaning and by keyword, then traverses the citation graph to surface not just similar passages but the authorities behind them — ranked, and correct as-of the date that matters.
Result. Research that returns the web of authority, every result grounded in a real, citable source.
Contract & clause analysis
The problem. Obligations, definitions and cross-references are scattered across long contracts and whole portfolios; manual review is slow and misses the links between a clause, its defined terms and the regulations it must satisfy.
Why GreyCat. Extract clauses and entities into the graph, link each to its obligations, defined terms and governing rules, and compare across an entire portfolio — with every version kept, so you can query any contract as it stood at signing.
Result. Clause-level insight and change tracking across thousands of documents at once.
Compliance & regulatory Q&A
The problem. Regulations change and cross-reference each other; an assistant that isn't grounded in the current text — or the text as it stood on a past date — invents answers your compliance team can't rely on.
Why GreyCat. Ground an AI assistant in the regulation graph through the built-in MCP server: it answers in plain language, cites the exact article, and is point-in-time correct — the rules as they applied on any date you ask about.
Result. Regulatory answers your team can trust, every one traceable to a citation and a moment in time.
Developed with the Court of Justice of the European Union — a pilot bringing GraphRAG to EU case law: citation graph, hybrid search and a built-in MCP server, all from one self-hosted binary. Explore it live ↗ · Read the case study →