An Insurance Agent Cut Commercial Renewal Prep From About 100 to 18 Minutes With Claude Code
An independent agent ran 34 of 47 commercial renewals through a Claude Code script that pulls policy details out of PDFs, marks unsure fields for review and fills the forms, cutting average prep from about 100 to about 18 minutes.
Who this is about: Independent P&C insurance agency, commercial lines
What it takes
- Cost
- Free planClaude: Free plan. Pro is $20 a month billed monthly ($17 a month billed yearly), and Max starts at $100 a month. Team seats are $25 a month billed monthly.Price checked Oct 24, 2026 on claude.com. Prices change; check before you buy.
- Setup time
- A few daysOur estimate from the source, for one business.
- Skill needed
- Some tech skillsComfortable installing an app, pasting an API key or running a command.
Explain it simply
Renewing a business's insurance means copying lots of details out of long PDF documents into forms. An insurance agent had Claude Code, an AI that writes small programs, make a tool that pulls those details out automatically and marks anything it isn't sure about for him to check. Prep for each renewal dropped from about 100 minutes to about 18.
What was done
The agent exports renewal documents from Epic as PDFs. A Claude Code script extracts the policy fields to JSON and marks any value it isn't sure about as "needs_review" instead of guessing. The agent checks the flagged fields, and the script then fills carrier submission packages and the comparison spreadsheet.
How it went
Over two weeks, 34 of 47 renewals went through the workflow, and average prep dropped from about 100 minutes to about 18, including review. The review flag caught 3 extraction errors before submission: two deductibles and one missed additional insured.
- Stacked umbrella schedules, old scanned documents and handwritten endorsements still have to be done by hand, which is why 13 renewals stayed manual.
- The post's title rounds the result to "2hrs to 15min."
Prompt
"Read each PDF in /renewals/[account]. Extract: named insured, policy number,
effective dates, coverages and limits, deductibles, additional insureds,
and 5-year loss runs. Output JSON. If a value is unclear, missing or could be
read two ways, set it to "needs_review" with the page number. Never guess a
limit or deductible."
Then: fill the carrier submission template and the comparison spreadsheet
from the reviewed JSON.
Our version of the workflow the post describes. The script itself wasn't shared.
Business fit
Who this helps, and how:
Independent contractors (barbers, bartenders, consultants): pull key terms from client contracts into one comparison sheet, with unclear items flagged.
AgenciesAgencies and freelancers: turn recurring client paperwork into structured data and fill your standard templates from it.
AgenciesMedical and health professional business owners: pull fields from insurer or vendor PDFs into a checklist, with uncertain values marked for staff review.
Local & serviceLocal service businesses: compare supplier or insurance quotes side by side without retyping each PDF.
Local & service
Related
- Evidence grade BA Cake Studio Went Live on a Claude Code-Built Order System in 12 DaysStrong evidence, using Claude Code, Claude and Next.js on Vercel
- Evidence grade DA Headshot Studio Replaced 5 Apps and $750 a Month in Software With a Claude Code ToolLight evidence, using Claude Code
- Evidence grade DA Machine Shop Owner Built an Offline Job Scheduler for 22 Machines With ClaudeLight evidence, using Claude, Claude Code and Git
- AI use cases for business operationsDepartment hub: AI for operations, 57 examples
Similar tools
Other tools for this job, and how they differ. Chosen by our editors, never paid for.
- ChatGPT
Upload dec pages and loss runs and ask for structured output, without writing a script.
- Google Document AI
Structured extraction from PDFs at higher volume.
- Nanonets
No-code document extraction into structured fields.
“Light evidence” (grade D) means: A brief, early or in-progress claim. Treat it as an idea to test, not proof. How we grade. Spotted a mistake? Suggest a correction.
