For in‑house counsel & legal ops

Your contract stack, distilled into one reliable answer.

AIAM Graph RAG reads across playbooks, policies, and hundreds of executed agreements to draft long‑form answers your lawyers can actually trust.

Keeps answers scoped to your documents with page‑level citations.
Built for contract work

Answer questions like:

  • “How do our most‑favored‑nation clauses differ across top customers?”
  • “Summarize data processing obligations across our European DPAs.”
  • “Compare termination for convenience provisions in these five vendor contracts.”
Behind the scenes, our agent searches pages, clauses, and tables across your agreements, then assembles a single, cited answer.
Use cases

Give every lawyer a contract analyst.

Surface obligations, compare clauses, and answer cross‑matter questions without paging senior counsel every time.

In‑house teams

Policy & playbook alignment

Ensure outside paper and negotiated language stay aligned with your internal playbooks and risk guidelines.

  • Ask “Does this clause violate our standard position?”
  • Trace every answer back to specific provisions.
Law firms

Matter‑aware knowledge base

Turn closing sets, memos, and negotiated templates into a graph your associates can query in plain language.

  • Reduce ramp‑up time on new matters.
  • Reuse reasoning from prior deals safely.
Legal ops

Obligations & risk mapping

Ask graph‑level questions like “Where do we owe uncapped indemnities?” or “Which contracts reference this policy?”.

  • Cross‑document entity and keyword graph.
  • Vector search over clauses and questions.
Who benefits

Put this in the hands of:

  • General Counsel and Deputy GCs who need fast, reliable portfolio‑level views.
  • Legal operations leaders looking to systematize institutional knowledge.
  • Mid‑level and junior associates doing clause comparisons and issue spotting.
  • Commercial and procurement teams answering contract questions from the business.
Why graph RAG works for legal

Contracts are naturally graph‑shaped: documents reference policies, schedules, and prior amendments. Our Neo4j schema captures those links, and the agent understands how to move between them when it answers.

Because the system reads across many pages and documents, it can answer nuanced questions – like how a concept is treated across your templates, or what changed between two rounds of paper – with an explanation, not just snippets.

Try multi‑turn legal Q&A