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Case Studies / Underwriting intake
Build Insurance

Underwriting intake as a governed AI workflow

A high-friction submission process rebuilt as an agentic workflow that organizes information, surfaces the evidence underwriters need, and routes decisions, with human oversight and audit built in from the first step.

Client Global insurance carrier
Industry Commercial insurance
Engagement Embedded delivery pod
Services AI Systems & Solutions, AI-Native Engineering
[01] The challenge

Submissions arrived faster than the team could read them.

Every commercial submission landed as a pile of email, PDFs, and spreadsheets in inconsistent formats. Underwriters spent the majority of each file rekeying data and hunting for the few facts that actually drove a decision.

The backlog grew, quote turnaround slipped, and good risks were lost to faster competitors. Off-the-shelf automation had been ruled out, the process was too regulated, and every decision needed to be explainable and auditable.

The constraint

Speed could not come at the cost of oversight. Nothing could reach a customer without a human in the loop and a record of why.

[02] The approach

One method, run end to end: Align, Make, Prove.

Align

Find the highest-leverage first move

We mapped the intake process with underwriting, IT, and compliance, then agreed on a single bounded slice to ship first, and the metric that would prove it worked.

Make

Build it into the real workflow

An embedded pod built an agentic pipeline that reads each submission, extracts and structures the data, flags gaps, and assembles a decision-ready package inside the systems underwriters already use.

Prove

Measure, govern, and expand

Every run was logged and reviewable. We measured against the baseline, tuned with underwriters in the loop, and only widened scope once the numbers and the audit trail held up.

[03] What we built

An intake copilot, not a black box.

The workflow does the reading and assembling; the underwriter still makes the call. Each submission becomes a structured, evidence-backed package with a clear recommended next action and a complete record of how it got there.

01

Ingests email, PDF, and spreadsheet submissions in any format

02

Extracts and structures the fields underwriting actually uses

03

Flags missing or conflicting information before it reaches a person

04

Logs every step for compliance, with a human approving each decision

[04] The accelerator Reusable

What we built became a NextAmp accelerator.

The intake workflow is packaged as three composable capabilities. Adopt the full pipeline, or start with the single capability that removes the most friction, each runs on its own and slots into the systems you already have.

01

Appetite triage

Scores each submission against underwriting appetite the moment it arrives, so teams spend their time on the risks actually worth quoting.

Available standalone
02

Submission completeness

Checks every submission against what underwriting needs and flags missing or conflicting information before it ever reaches a person.

Available standalone
03

Risk enrichment

AI-assisted enrichment that augments the risk profile with relevant public data, giving underwriters fuller context automatically.

Available standalone
[05] The results
80%

Faster time to quote on the submissions the workflow handles.

65%

Reduction in manual data entry, freeing underwriters for judgment work.

1 qtr

From kickoff to a governed workflow running in production.

“It shipped in a quarter, and the numbers moved. Just as important, every decision is explainable, our regulators can see exactly how we got there.”

VP Underwriting · Global insurance carrier

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Have a constraint like this one?

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