Integration
Contract Review Automation — Custom AI for Your Playbook
AI that reviews contracts against your firm’s own clause playbook — extracting terms, flagging risk and missing provisions — with a lawyer in the loop and every decision logged.
Contract review automation uses AI to read contracts and extract the clauses, obligations and risk against your firm’s own playbook — flagging missing or non-standard provisions and routing anything ambiguous to a lawyer — so review scales without associates re-reading the same paper, and without a generic tool that doesn’t know your standards.
The problem
Why generic contract-review tools underperform
Manual contract review is the classic associate time-sink, but the off-the-shelf tools that promise to fix it review against a generic playbook — so they flag what a generic firm cares about, not what yours does. Your fallback positions, your risk thresholds, the clauses you never accept: that institutional knowledge is the actual value, and a SaaS template can’t hold it.
We build review tuned to your playbook. The AI extracts terms and clauses, compares them to your standards, flags non-standard language and missing provisions, and writes structured results back into your DMS — with low-confidence items routed to a lawyer so accuracy climbs without removing judgement.
The solution
Where automation removes the friction
What the system does
Clause and term extraction against your taxonomy; risk and deviation flagging relative to your fallback positions; missing-clause detection; and a structured summary written back to iManage/NetDocuments or your contract store. It grounds every extraction in the source text, so a reviewer can click straight to the clause rather than trusting a black box.
Accuracy with a lawyer in the loop
High-confidence extractions flow straight through; anything ambiguous routes to human review, and the system learns from the correction. Everything runs in your environment with audit trails, so output is defensible.
Example workflows we build
- Clause & term extraction against your playbook
- Risk and non-standard-clause flagging
- Missing-clause detection
- Structured summary write-back to iManage/NetDocuments
- Human-in-the-loop review with learning from corrections
The results
The commercial impact
Our approach
From manual to automated
- 01Encode your playbook
We turn your clause standards, fallback positions and risk thresholds into the schema the AI reviews against.
- 02Build extraction & flagging
Clause/term extraction, deviation and missing-clause detection, grounded in the source text.
- 03Validate with human-in-the-loop
We test on real contracts and route low-confidence items to a lawyer until accuracy meets your bar.
- 04Integrate & deploy
Structured results write back to your DMS/contract store, inside your environment, with audit trails.
Why a custom build beats off-the-shelf
- Reviews against your clause playbook and fallback positions — not a generic standard.
- Every extraction is grounded in the source clause, so it’s traceable and defensible.
- Runs in your environment; contract data never leaves or trains a public model.
- Improves as lawyers correct it, instead of staying static.
Frequently asked questions
How is this different from off-the-shelf contract-review software?
Off-the-shelf reviews against a generic playbook. We encode your firm’s clause standards, fallback positions and risk thresholds, so it flags what your firm actually cares about — and it writes back into your DMS instead of a separate silo.
Can it detect missing clauses, not just risky ones?
Yes — missing-clause detection against your expected set is a core part of the build, alongside non-standard-language flagging.
How accurate is it, and is it defensible?
Every extraction is grounded in the source clause so a reviewer can verify it, low-confidence items route to a lawyer, and the system learns from corrections. Output is traceable and audit-logged.
Where does our contract data go?
It stays in your environment with role-based access and audit trails; nothing leaves your boundary or trains a public model. We work under NDA.
How long does it take?
Most builds go live in 6–8 weeks, depending on how much of your playbook we encode up front.
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 free audit for a clear price and ROI estimate.