Contracts, matter files, filings, and regulatory correspondence each hold part of your institutional knowledge. None of them holds the whole. LangOptima ingests the legal documentation you already have and connects it into a single knowledge graph, so clause exposure, obligations, and prior positions become questions answered in seconds, with a citation back to the source document.
The approach behind legislation.gov.uk, which publishes all UK law as RDF Linked Data, so Acts, sections, and their versions connect as data instead of static pages.
A counterparty triggers a dispute, or a regulation changes, and someone asks which agreements are affected. In many legal teams, the answer is still: “Someone will have to read through them.”
Every contract, filing, and memo is self-contained. The document management system stores files, not the relationships between them. What one agreement establishes never reaches the next matter that needs it.
When a regulation changes or a counterparty position shifts, someone re-reads the portfolio to find which agreements carry the relevant clause. The work repeats for every new question, and the findings evaporate when the matter closes.
Renewal windows, indemnities, change-of-control triggers, notice periods: scattered across thousands of agreements in inconsistent language. A missed obligation is usually discovered at the moment it bites.
LangOptima ingests the legal documentation you already hold: contracts, matter files, case documents, regulatory correspondence. It structures the parties, clauses, obligations, dates, and defined terms inside them into a semantic knowledge graph that sits above your document management system without replacing it. A question that once meant a week of document review becomes a single query with source citations.
Modern AI can structure a great deal on its own. Where it stops is the meaning specific to your organization: the concepts, rules, and relationships that make your business yours, and where its real value lives. We structure that layer with you on open, world-standard semantics, not a proprietary schema, so the graph reflects how you operate and stays yours: no vendor lock-in, portable to whatever you run next. More on the structure beneath it →
You don't have to boil the ocean. Start with a single business context and prove it there. Once that foundation is laid properly, the same connected data tends to open opportunities in other departments, so the next team builds on the work already done rather than starting from zero.
Contracts, matter files, filings, and correspondence unified at the semantic layer. Nothing moves. Nothing is replaced. Your document management system keeps doing its job.
Traverse from a clause to every agreement that carries a variant of it, from a counterparty to every matter it appears in, from a regulation to every obligation it touches: relationships no folder structure can hold.
“Which agreements carry this indemnity?” answered in seconds, each result citing the exact document and clause, instead of a week of manual review that starts from zero every time.
Every lawyer works with the institution's full memory behind them. New team members query years of negotiated positions and precedent from day one, instead of relearning them matter by matter.
Representative scenarios of how legal teams apply a knowledge graph over their documentation. Illustrative of the pattern, not published client references.
An in-house team facing a transaction needs to know which of its agreements carry change-of-control triggers or uncapped indemnities. With the portfolio connected in a knowledge graph, the review becomes a query across structured clauses, each hit citing the agreement, the clause, and the counterparty, rather than a document-by-document read.
A regulatory change lands and the team needs to know where it applies. Because obligations, defined terms, and parties are structured in the graph, the question runs as one traversal, from the regulation's subject matter to every affected agreement, with a source trail an auditor or regulator can follow.
However complex the document landscape underneath, the engagement itself stays simple.
Pick one decision that matters, say your exposure to one clause across every live agreement. We build the knowledge graph over the contract, matter, and filing systems you already run. Nothing is replaced. Your teams keep working where they work today.
Your team's questions, reports, and AI run on that connected layer. Answers come in seconds, accurate and traceable, with citations back to the exact document and clause.
A working result in a scoped 8–12 week paid pilot, measured against success criteria you set. If it proves value, you expand from there. If it doesn't, it doesn't scale.
A 30-minute conversation about your document landscape: which systems hold your agreements and matters, and what a connected view of them would answer first. No deck, no pitch.
The same connected-data approach, applied across sectors. Explore another industry.