Review turnaround
Turnaround = review complete date - contract received date, averagedShows how quickly contracts get a first review.
An AI contract intelligence agent is software that reads contracts to extract key terms, summarise them, compare versions and flag clauses that depart from your playbook.
A contract is added to the repository.
The agent identifies type and extracts key terms.
It compares clauses with the playbook.
It writes a findings summary with sources.
Legal or the owner decides which findings to act on.
Terms and decisions are saved to the contract record.
The contract intelligence agent reads contracts, amendments, order forms and prior versions. It identifies the document type, extracts key terms, reads clauses on liability, indemnity, termination, data and service levels, and compares them with your playbook and clause library. It also compares versions and answers questions across the repository.
Reviewers get a short summary, a ranked list of departures and suggested fallback wording, each linked to the clause text. Legal gives the advice, buyers negotiate, owners set the playbook and signatories sign. People review and send any language. The agent stores extracted terms with citations and logs every extraction and comparison it runs.
Each task below is something the agent prepares, checks, drafts or routes, with a person keeping the decision.
It pulls parties, dates, pricing, payment terms, term length and notice periods into a record.
It compares clauses with your preferred language and fallbacks, and marks what differs.
It highlights clauses on liability, indemnity, termination, data protection and auto-renewal, with the source text.
It summarises long documents and shows what changed between versions or against a template.
It finds and cites the clause that answers a question about a contract.
It reads contract documents, amendments, order forms, your clause library and playbook, and prior versions.
It decides what type of document it is, which clauses match or depart from your standards, and how to rank the findings.
It extracts and stores terms, drafts summaries and suggested redlines, and answers questions with citations. People review and send any language.
Identifies contract type and pulls key terms.
Reads liability, indemnity, termination, data and SLA clauses.
Compares drafts with your standards and suggests fallbacks.
Shows version differences and short summaries.
Finds and cites answers across the repository.
Bring a small sample and watch Flo work through it.
| Aspect | By hand | With the agent |
|---|---|---|
| Reading | Reviewers read full documents for key terms. | Key terms are extracted with page references to check. |
| Playbook use | Applied from memory and varies by reviewer. | Clauses are compared with the written playbook every time. |
| Comparison | Versions are compared by eye. | Differences between versions are listed and summarised. |
| Search | Finding a clause means opening files. | Questions are answered with cited passages. |
| Data quality | Records are keyed late and unevenly. | Contract data is populated and flagged for confirmation. |
| If | Then | Who decides |
|---|---|---|
| A clause departs from the playbook position | It flags the clause and shows the preferred wording | Legal reviewer |
| Liability or indemnity terms are unusual | It raises the finding to the top of the summary | Legal counsel |
| A required clause is absent | It lists the gap and suggests what is missing | Legal reviewer |
| A term conflicts with a master agreement | It shows both passages side by side | Contract owner |
| Extraction confidence is low | It marks the field as unconfirmed | Contract admin |
| The document type is unclear | It asks for classification before analysis | Contract admin |
Text may be misread, so values are marked low confidence. A person verifies against the document.
The agent compares the latest text to the prior version and summarises changes. Legal decides acceptability.
Terms are extracted with a caution on translation. A qualified reviewer confirms meaning.
It is shown as unclassified, not scored. Legal decides if the playbook needs updating.
Talk it through with the team. We will map it to your steps and show where a person stays in control.
Start with key terms on new contracts and have the admin confirm them.
Apply the playbook to one contract type, with legal checking every finding.
Offer version comparison and cited questions to the legal team first.
Extend to older contracts in batches, prioritising those with near renewals.
Turnaround = review complete date - contract received date, averagedShows how quickly contracts get a first review.
Highlights where counterparties push back on your standards.
Indicates how reliable extracted data is for your documents.
Quick answers to what people ask most about AI contract intelligence agent.
Book a demoIt is an agent that reads contracts, extracts their terms, compares them with your playbook and flags risk. It makes contract data searchable. Legal and procurement decide.
No. It speeds up reading and highlights departures. Lawyers decide what is acceptable and how to respond.
Yes. It can read order forms, MSAs and amendments, and flag terms such as auto-renewal, price uplifts and data clauses.
No. It can route a contract to its signatories, but only authorised people sign.
An AI contract obligation agent is software that extracts what each party has agreed to do from a contract, such as deliverables, deadlines, usage commitments and pricing, and tracks whether it is being met.
→An AI agent for contract renewal is software that tracks contract end dates and notice periods, alerts owners ahead of deadlines, and prepares the information needed to decide whether to renew, change or cancel.
→Contract pricing validation is the check that the prices, rates, discounts and fees written into a contract match what was quoted, ordered and later billed.
→Contract template selection is the step of choosing the correct starting document for a new agreement, such as an NDA, master services agreement or order form, based on what is being bought.
→Bring a small sample of real items. We will show what Flo handles on its own and where it hands over to your team.