Use case
Contract review is the highest-value place AI can help. Also the highest-risk place to paste it into a chatbot.
Reading contracts thoroughly is expensive time. AI can meaningfully compress it — extracting key clauses, flagging unusual provisions, producing plain-English summaries. It is also the point at which the most commercially sensitive material a firm handles enters the request: the executed agreement, the deal terms, the schedule identifying the parties. The productivity case is obvious; the confidentiality case is why on-premise fits this task particularly well.
Request an assessmentWhat the work looks like today
Before AI
A lawyer, contract manager or in-house counsel opens the executed PDF, reads it end-to-end, marks up the interesting clauses, and writes a summary or file note. On a 60-page master services agreement with 10 schedules, that is a serious afternoon of work, and it happens on every negotiation that goes anywhere.
The shortcut everybody's already taking
With a public chatbot
The pasted-into-chatbot version is quick and useful — and it transmits the parties, consideration, term, termination triggers, confidentiality clauses, IP allocation and dispute mechanism to a third-party service. For a public tender the counterparty may not care. For an M&A term sheet, an executive employment contract or a settlement deed, that is a set of facts you agreed in writing not to disclose.
Same job, done properly
The on-premise version
Same clause extraction, same summarisation, same risk flagging — with the contract text never leaving your firm's network. The system can be pointed at a folder of executed contracts so you can also ask retrospective questions ("what force majeure carve-outs did we accept last year?") without transmitting the corpus anywhere.
Where it lands
Concrete applications
Corporate and commercial legal
M&A term sheets, SPAs and shareholder agreements; distribution and reseller agreements; commercial supply arrangements. Every clause in these is confidential by default and often bound by a mutual NDA in addition.
In-house counsel and contract managers
Vendor MSAs, statements of work and consulting agreements. AI extraction of dates, termination triggers, indemnity caps and payment terms lets a small legal function cover a much larger contract volume without hiring.
Property and construction
Head contracts, subcontracts, D&C schedules. The variation and dispute exposure alone justifies a proper AI-assisted review flow — done on infrastructure your clients trust.
Employment and executive contracts
Individual employment agreements, executive service contracts, separation deeds. Deeply personal and commercially sensitive; obviously unsuitable for cloud AI.
Insurance and reinsurance
Wordings, treaty schedules, endorsement bundles. Confidentiality and commercial competition make the cloud AI analysis particularly sharp here.
Contract review: common questions
- How accurate is AI contract review compared with a lawyer?
- For structured extraction (dates, parties, monetary amounts, defined terms) it is accurate enough to be useful with a fast lawyer sanity-check. For clause interpretation and risk judgement, it is a first pass — good enough to surface unusual provisions for human attention, not good enough to replace the human review. Any vendor telling you otherwise is overselling; that includes us.
- Can the system compare a draft against our internal precedent bank?
- Yes — this is one of the strongest use cases. The precedent bank lives on your system, the incoming draft never leaves, and the analysis happens locally. This is the kind of workflow that most obviously breaks the "just use ChatGPT Enterprise" logic, because a large precedent library is exactly the kind of data you don't want offshored to make a query work.
No obligation
Interested in contract review specifically?
Tell us the volume and the sensitivity, and we'll tell you honestly what an on-premise setup would look like for this particular workload.