You sit where the company’s exposure lands. Contracts that have to be read before they’re signed. Claims that have to be triaged before they age. Insurance submissions and renewals that have to be airtight before they reach an underwriter. Compliance obligations that don’t move just because your team is short-staffed.
And the volume keeps climbing while the headcount doesn’t. You’re being asked to review more documents, close more gaps, and stand behind more decisions — with the same two or three people who already work nights at renewal time. The risk isn’t just missing something. It’s that the routine work crowds out the judgment work, and the judgment work is the part nobody else can do.
That’s the seat AI is actually good for. Not replacing your read of a tricky indemnity clause — accelerating everything that surrounds it so you get to the clause faster, with cleaner inputs, and a record of how you got there.
Where AI earns its keep for your function
The pattern that works for legal and risk is narrow and disciplined: point AI at the high-volume document and intake work, let it do the cognitive first pass, and route every exception to a person. AI prepares. A person approves. The system logs. For anything touching money, customers, or commitments, that loop is non-negotiable — and it’s also what makes the output defensible when someone asks how a decision was made.
Done right, this gives your team back the hours currently lost to keying, sorting, and chasing — and gives you a cleaner, more complete record than manual work ever produced.
Common use cases
Contract & document review
AI reads inbound contracts, NDAs, MSAs, leases, and vendor agreements; extracts the terms that matter — liability caps, indemnification, auto-renewals, governing law, payment terms — and flags clauses that deviate from your playbook. Your reviewer opens to the issues, not to page one. Teams often see review time drop sharply on routine agreements, with attention freed for the genuinely thorny ones.
Submission & policy intake
For brokers and carriers, AI pulls structured data out of submissions, applications, ACORD forms, and policy documents and lands it in your system of record — with low-confidence fields routed to a human queue. Intake that used to bottleneck the underwriting desk moves same-day instead of same-week.
Claims triage
AI reads incoming claims documents — first notices, supporting records, correspondence — classifies and prioritizes by severity and complexity, and surfaces the ones that need a senior eye now. Adjusters and examiners spend their time on judgment and exceptions, not on sorting a queue.
Insurance renewal preparation
Renewals have become some of the hardest commercial conversations going. AI assembles your actual posture, documents controls and evidence, identifies gaps before an underwriter does, and drafts the questionnaire responses and submission narrative for your review. Teams typically cut renewal prep from weeks of senior time to a fraction of it — and walk in with documentation that positions them better, not just faster.
Compliance & governance documentation
AI drafts attestations, control evidence, policy documentation, and audit-ready records from what’s actually in place — keeping the paper trail current instead of scrambling to reconstruct it before an audit or exam.
Obligation & deadline tracking
AI extracts obligations, renewal dates, and reporting deadlines from your contract and policy base and keeps them visible — so nothing auto-renews, lapses, or breaches because it lived in one person’s inbox.
A note on the numbers: these outcomes are directional, drawn from how this work tends to go — not guarantees. The right scope for your volume is a conversation, not a brochure figure.
How we ship it
Two ways in, and most legal and risk leaders use both.
Value Sprints are how we build a specific workflow — contract review, claims triage, renewal prep — as a fixed-fee build shipped in weeks, tied to one measurable KPI and backed by our 12-month KPI guarantee. We sample your real documents, build the extraction and review layer, integrate with your system of record, and stand up the human-review queue. Narrow scope, real production, no science projects.
AI Office is how you run it afterward — a senior partner on retainer who operates the workflow, tunes it as your documents and obligations change, and finds the next thing worth building. Tiers run Sherpa at $2,500/mo, Operator at $5,000/mo, and Embedded at $10,000/mo, month-to-month with no minimum term. It’s less than a single internal AI hire, and you get a team that’s done this across 100+ companies instead of one person learning on your time.
Not sure where the highest-value workflow is hiding? The AI use-case canvas and a quick look at our approach are good places to start.
A word on trust
Everything in this seat has to hold up under scrutiny — to a regulator, an auditor, an underwriter, or opposing counsel. So we build for that. AI handles the first pass; a person owns the decision; the system keeps the record. Human-in-the-loop isn’t a feature we bolt on for legal work — it’s the design. You stay in control of every call that carries consequence, and you get a cleaner audit trail than manual review ever left behind.
We’ve done this across more than 100 middle-market companies over 20+ years, with a 96.5% project success rate against a 16.2% industry average. We’re not interested in the demo. We’re interested in the workflow that’s still running — and still defensible — a year from now.
Let’s talk
If document volume, claims backlog, or a renewal on the calendar is eating your team’s judgment time, a short conversation is the right first step. We’ll tell you straight whether a Sprint makes sense for your specific situation.