Due diligence & contract review
AI reads contracts and filings, flags risk clauses, and writes structured findings back into iManage or NetDocuments.
60–80% less manual review time per matter
Use case · By industry
Legal AI Automation for Regulated Law Firms
Regulatory intelligence, legal RAG over your own matters and precedents, and due-diligence automation — built as secure, auditable AI systems that run inside the environment your firm already controls.
Legal AI automation puts custom AI to work on a law firm’s highest-volume manual work — monitoring regulators for relevant changes, answering questions across your matters and precedents through a private RAG system, and extracting risk from contracts and filings — all inside a deployment you control, with a full audit trail on every action.
The problem
The problem: legal knowledge work doesn’t fit off-the-shelf AI
A regulated practice runs on two things generic AI tools cannot touch: confidential client data that legally cannot leave systems you control, and a body of knowledge — matters, precedents, regulatory positions — that no public model has ever seen. A ChatGPT subscription cannot read your matter history, and it certainly cannot be trusted with privileged documents.
So the manual work stays manual. Analysts spend their day watching regulator websites for circulars that might affect a live matter. Associates re-read the same contracts to pull the same clauses. The knowledge sits in a DMS that can store a document but cannot answer a question about it. Capacity is capped by headcount, and the firm reviews fewer matters than it could.
- Associates burning hours on manual document review
- Risk clauses slipping through under deadline pressure
- Due-diligence cycles that don’t scale with deal flow
- Matter intake bottlenecked on paralegal triage
- Sensitive client data that can’t leave your DMS
- No audit trail across thousands of documents
The solution
Where automation removes the friction
Matter intake & classification
Incoming documents are auto-classified and routed to the right matter and team without paralegal triage.
Hours saved on every new matter
Compliance & audit trail
Every extraction is logged and reviewable inside your existing security perimeter.
Audit-ready on every document
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.
Example workflows we build
- Continuous regulatory-change monitoring (SEBI, RBI, exchanges, sector circulars) mapped to affected matters
- Private legal RAG: ask questions across your matters, precedents and filings, with citations
- Contract & due-diligence extraction — clauses, risk, liabilities — written back to iManage/NetDocuments
- Automated matter intake and document classification
- Precedent database with relearning as new matters close
- Audit-trail and access-control layer over every AI action
The results
The commercial impact
90%
Less time on manual regulatory monitoring (litigation-firm build)
5×
Faster internal response to regulatory changes
100%
Audit-trail coverage on every AI action and extraction
Weeks
Typical time to go live, not months
Fixed-price
Scoped to outcomes, ROI agreed up front
Human-in-loop
Review on exceptions, full audit trail
Our approach
From manual to automated
- 01Discovery & security scoping
We map the manual workflow — regulatory monitoring, review, intake — and agree the deployment and security model (your tenancy vs. a dedicated instance) before any build.
- 02Ingest & index your knowledge
We load matters, precedents and documents into a private vector database, so the AI answers from your context, with citations.
- 03Build the workflows
Regulatory monitoring, RAG Q&A, contract extraction and risk-flagging — tuned to your practice areas, with human-in-the-loop on low-confidence items.
- 04Deploy, audit & relearn
Go live inside your environment with role-based access and full audit trails; the index relearns as matters close and precedents are added.
Why a custom build beats off-the-shelf
- Runs inside your environment — privileged client data never leaves systems you control and never trains a public model.
- Answers from your own matters and precedents (private RAG), not a generic model that has never seen your work.
- Deployed on your DMS and your security model (iManage/NetDocuments, role-based access) instead of a one-size SaaS.
- Every action is logged for an audit trail you can put in front of a regulator or client.
Frequently asked questions
Where does our data live, and could it leak into a public AI model?
It lives where you decide — your own cloud tenancy or a dedicated, isolated instance (e.g. OpenAI on Azure, a private model, or your own). Privileged data never leaves that boundary and never trains a public model. We scope this before any build.
What is legal RAG, and why not just use ChatGPT?
RAG (retrieval-augmented generation) means the AI retrieves the exact passage from your own matters or precedents and cites it, instead of guessing. A public chatbot has never seen your work and cannot be trusted with privileged documents — a private RAG system answers from your context, with an audit trail.
Can it really track regulatory changes like SEBI and RBI circulars?
Yes — that is exactly the system we built for a top corporate litigation firm. It monitors regulator and exchange sources continuously, classifies each change by relevance, and maps it to the matters it affects, cutting manual monitoring time by ~90%.
Does this work with our existing iManage or NetDocuments setup?
Yes. We build on top of your current DMS rather than replacing it — your security model, folder structure and access controls stay intact.
How accurate is AI extraction on legal documents?
We pair OCR/LLM extraction with validation rules and human-in-the-loop review for low-confidence items, so accuracy improves over time without taking a lawyer out of the loop.
How long does a build take?
A focused workflow goes live in 4–6 weeks; a full RAG-plus-monitoring system is typically 8–12 weeks depending on the volume of matters to ingest and your security requirements.
What does it cost?
Engagements are fixed-price and scoped to the outcome. Every engagement is fixed-price with ROI targets agreed up front, backed by our 90-day ROI guarantee. Book a discovery call. for a clear price and ROI estimate.
Related use cases & services
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