AI Document Review & Due Diligence for Law Firms

What we built for a top corporate litigation firm

For one of the largest corporate litigation practices in India, the bottleneck was regulatory intelligence. Analysts manually monitored a long list of government and regulator sources — SEBI, RBI, the stock exchanges, and sector circulars — then tried to connect each change back to the right live matter by hand. Slow, and easy to miss.

We built a regulatory-intelligence system that watches those sources continuously, classifies each new circular or order by relevance, maps it to the matters it actually affects, and surfaces it to the responsible team with the source attached. The matter and precedent knowledge lives in a private vector database, so the AI answers from the firm’s own context rather than guessing. The result: 90% less time spent on manual monitoring and a 5× faster internal response to regulatory change — with no document ever leaving the firm’s environment.

The architecture: legal RAG over your own matters & precedents

The core is a private RAG (retrieval-augmented generation) system. We ingest your matters, precedents, contracts and filings into a vector database, so an AI can retrieve the exact passage that answers a question and cite where it came from — instead of producing a confident hallucination. As matters close and precedents are added, the index relearns, so the system gets more useful over time rather than going stale.

On top of that sit the workflows that do the work: regulatory monitoring, contract and due-diligence extraction, matter intake, and clause-level risk flagging. Low-confidence items route to a human for review (human-in-the-loop), so accuracy improves without ever taking a lawyer out of the loop on the things that matter.

Security & compliance: the part that actually decides the deal

For a regulated firm, “where does the data live” is the first question, not the last. We deploy inside an environment you control — your cloud tenancy or a dedicated, isolated instance (OpenAI on Azure, a private model, or your own) — so privileged data never trains a public model and never leaves your boundary. Role-based access mirrors your matter-level permissions, and every AI action, extraction and answer is logged for a complete audit trail you can show a regulator or a client.

Due diligence, contract review & DMS integration

The same foundation powers document-heavy work. We deploy OCR and LLM extraction that parses contracts and filings, flags risk and liability clauses, tags metadata, and writes the structured result straight back into iManage or NetDocuments — building on your existing document management system instead of forcing a new platform on your associates. Due-diligence cycles drop from days to hours, and matter intake stops being a re-keying exercise.

An alternative to outsourced document review

Firms with review volume that outpaces headcount usually have one lever today: send the batch to an outsourced review vendor or an LPO and pay by the document or the hour. That works, but it means privileged material leaves the firm, turnaround depends on someone else's staffing, and the cost scales with volume forever.

This is a different lever, not a request to trust a vendor with client data. The first-pass read — flagging risk clauses, extracting key terms, surfacing what actually needs a lawyer's attention — happens inside your own environment, on your own DMS, with nothing sent externally. Associates review what the system flags as uncertain instead of every page of every document. It doesn't replace judgment on a matter that needs it; it removes the part of the batch that never needed a person in the first place.