Finding information in contracts has traditionally meant reading. Someone opens the agreement, searches for a likely word, reads the clauses around it and works out what they mean. It is slow, error prone and mostly limited to people with legal training, so business teams wait in the legal queue for simple answers.
AI contract inquiry changes how people interact with contracts. Legal and business users ask questions in plain language, such as whether they can end a contract early or what the supplier must deliver this quarter, and get a direct answer with the relevant clause highlighted. This guide explains how it works, what it can answer and how to use it responsibly.
How does AI contract inquiry work?
AI contract inquiry is an assistant that sits on top of your contracts. It uses natural language processing and large language models to understand your question, find the relevant parts of the contract and explain them in plain language.
Unlike keyword search, it works from meaning. Ask about late payment penalties and it finds the clause even if the contract calls them interest on overdue amounts. Ask whether you can exit early and it looks at termination for convenience, notice periods and any fees that apply.
How do people use it?
- Ask in plain language: type a question the way you would ask a colleague.
- Upload and ask: add a contract that is not yet in the repository, such as a counterparty draft, and ask questions about it.
- Explore: move from an answer to the clause, related obligations and connected documents such as amendments.
What can you ask a contract?
| Question type | Example | What you get |
|---|---|---|
| Clause meaning | What does the limitation of liability clause cover? | Plain language summary with the clause |
| Rights and obligations | What must the supplier deliver each quarter? | List of obligations with dates |
| Key dates | When is the notice deadline for renewal? | Date and the clause that sets it |
| Risk | Does this contract allow unilateral price increases? | Yes or no, with the relevant terms |
| Compliance | Does this agreement include our required data protection terms? | Comparison with your standard |
Questions can cover one contract or, with Aavenir Atlas, the whole portfolio, such as which supplier agreements renew in the next quarter.
What are the benefits?
1. Time saved across the lifecycle
Instead of reading pages to find a late payment clause, users ask and get the section at once. The saving applies at every stage, from negotiation to managing the contract after signature.
2. Compliance checks
AI can compare a contract with your policies and connected data, such as governance, risk and compliance requirements, and point out where it may not align.
3. Risk spotting
AI flags clauses that carry risk, such as unfavorable termination terms or hidden fees, and can draw on past contracts to suggest better positions for the next negotiation.
4. Visibility of obligations
Asking what each party must do, and by when, makes it easier to track performance and hold both sides to their commitments. See Obligationflow.
5. Better informed decisions
Users understand their position before they negotiate, renew or raise a dispute, which strengthens their hand.
6. Contracts connected to the business
Answers can draw on connected records such as amendments, sourcing events and invoices, and plain English explanations help people outside legal understand what they agreed. That reduces silos between legal and the business.
How do you trust the answers?
An answer is only useful if people can verify it. Three practices matter:
- Show the source: every answer should link to the exact clause it came from, so the user can read it in context.
- Respect permissions: the assistant should only search contracts the user is allowed to see.
- Know when to escalate: for questions that need legal judgment, such as whether a breach has occurred, the answer is a starting point for a lawyer, not a conclusion.
Aavenir's Avy answers questions inside Contractflow, natively on ServiceNow or standalone. It shows the source text with every answer, works within the user's permissions and logs each interaction. Customer contracts are never used to train external models.
Where should you start?
Start with the questions your legal team answers most often for the business: termination rights, renewal dates, liability caps and data protection terms. Let business users ask those directly, measure how many requests no longer reach legal and review a sample of answers each month to confirm they are accurate.
Load the contracts first. Inquiry works best on a complete repository, including amendments and side letters, because an answer drawn from the original agreement alone can be out of date. If legacy contracts still sit in shared folders, migrate the active ones and let AI extract their key terms before you open inquiry to the business.
Finally, publish a short guide for users: the kinds of questions the assistant answers well, how to read the source clause and when to send the question to legal instead. A little guidance early on builds the right habits.
The bottom line
AI contract inquiry lets anyone ask a contract a question in plain language and get an answer linked to the clause. It saves legal time, helps business users understand what they agreed and surfaces risks and obligations, provided every answer shows its source.