$318k a year back across eight insurance agencies
Quotes, policies, forms → read, check, file → straight into the AMS
Eight agencies ran on four different systems. Every quote, policy, and form was read and typed in by hand. The typing took ten minutes each. The waiting took far longer. In a busy week a document could sit for over a week, and by then the prospect had bought elsewhere. Now around 3,000 documents a month are read, checked, and filed automatically. That is 6,000 staff hours a year back, plus about 270 policies that used to go cold.
What it's worth
Staff time back
- Documents per month
- 3,000
- Hand-keying time per document
- 10 min
- Hours back per month
- 500 hrs
- Hours back per year
- 6,000 hrs
- Producer / CSR cost
- $35 / hr
- per year
- $210,000
Commission saved
- New-business quotes per month
- 750
- Share lost to slow replies
- 10%
- Quotes saved per month
- 75
- How many of those bind
- 30%
- Extra policies per year
- ~270
- Commission per policy
- $400 / yr
- per year
- $108,000
How this was calculated — every assumption
- Volumes come from the client: about 3,000 documents a month across the eight agencies, at roughly 10 minutes of hand-keying each.
- Producer and CSR time is costed at $35/hour. That is salary plus tax, benefits, and overhead.
- About a quarter of documents are new-business quotes. The rest only count toward staff time.
- The 10% covers quotes lost because the reply came too late, not quotes lost on price. Only 30% of those saved quotes are counted as binding.
- Renewal flagging is not in this total. It clearly saves policies, but we have no measured figure for it yet, so it is left out rather than guessed at.
- These are models built from reported volumes, not audited accounts.
Results at a glance
- ~$318,000 a year across eight agencies. About $40,000 each.
- 6,000 staff hours a year back
- ~270 policies a year that used to go cold, worth ~$108,000 in commission
- Turnaround now takes minutes, busy week or not
- Renewal tracking added: policies flagged before they come due, not after
- 8 agencies live across 4 different systems
The problem
The client runs eight independent agencies across four systems: AMS360, Applied Epic, EZLynx, and Dynamics. Producers read every incoming quote, endorsement, policy, and form, then typed the data into whichever system that agency used. Documents arrived as scanned PDFs, phone photos, and hand-filled forms. No two carriers used the same layout. The ten minutes of typing was the visible cost. The wait in front of it was the expensive one. How long a document sat depended on how busy the week was: minutes when things were quiet, over a week at peak. A prospect who waits a week has already bought somewhere else.
What was built
Read any format
Emailed PDFs, scans, phone photos. The pipeline pulls the fields out with AI, plus OCR for photos and handwriting. Nothing waits for a person to open it.
Check every field
Each result is checked against a strict schema. If it fails, it goes to a human review queue. Nothing half-formed reaches a policy system.
File it in the right system
Clean data is mapped into the shape each agency's system expects. APIs where they exist. Browser automation where they don't.
Flag renewals early
The same pipeline watches policy dates and flags renewals before they come due. Nobody finds out a policy lapsed after the fact.
Handle the next step
Routing, notifications, moving a document forward. All the follow-on work producers used to do by hand.
Log everything
Every run is logged. A test set of real documents runs against every change, so accuracy never slips quietly.
What keeps it from breaking
Nothing unchecked reaches your AMS
Validation is a hard stop, not a warning. Failed records go to a person, not into your policy system.
Accuracy is tested, not assumed
Real documents with known-correct answers run against every change. Quiet accuracy drift is the failure that would poison a book of business.
APIs first, browser automation second
Browser automation is more fragile. It only covers systems with no API, and it is monitored on its own.
How the approach worked
Keep it simple. Good prompting and clean API calls before anything custom. The hard part was never one model call. It was staying reliable across eight agencies, four systems, and documents that never look the same twice. And the value was never just the keying time. A ten-minute job that waits three days is a three-day job to the person waiting.
The results
About 3,000 documents a month now go through the pipelines instead of through a producer's hands. That is roughly 6,000 staff hours a year, worth about $210,000. Faster turnaround is worth more than it looks: around 270 policies a year that used to go cold now bind, worth about $108,000 in commission. Renewals get flagged before they lapse, and each agency keeps using the systems it already paid for.
Ten minutes of typing per document, behind a queue that ran from minutes to over a week. Eight agencies, four systems, all by hand.
Documents handled on arrival, checked, and filed automatically. Same turnaround whether the week is quiet or busy.
Tools & technologies
Have a process like this slowing your business down? Tell me your stack and goals and I'll send back a build plan.
Take the stack assessment →