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FinanceAIAutomation

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Insurance claims · United Kingdom

Key outcomeManual document entry fully eliminated
0
Manual data entry steps
94%
Document extraction accuracy
8x
Faster claim processing
The challenge

What needed
solving

A UK insurance claims handler was manually extracting data from 200+ PDF documents per day — policy numbers, damage estimates, claimant details — into their internal system. Errors were frequent and the team was at capacity.

The solution

What we built

We built a GPT-4o Vision pipeline that reads incoming claim documents from AWS S3, extracts all structured data with 94% accuracy, and pushes validated records directly to the case management database via n8n.

Tech stack
GPT-4o VisionPythonAWS S3PostgreSQLn8nResend
Sector
Finance
Category
FinanceAIAutomation
Results

The numbers

Concrete, measurable outcomes delivered in production.

0
Manual data entry steps
94%
Document extraction accuracy
8x
Faster claim processing
How we work

From brief to production

01

Discovery & scoping

We map the problem, understand the existing stack, and write a fixed-price proposal. No surprises.

1–3 DAYS
02

Build & weekly demos

You see working software every week. Feedback is incorporated immediately — not at the end.

2–6 WEEKS
03

Testing & QA

Every integration is stress-tested before go-live. Edge cases handled, fallbacks in place.

3–5 DAYS
04

Go live & handover

Full documentation, team training, monitoring setup, and 30-day post-launch support.

1 WEEK

Build something similar?

Book a free 30-minute call. We'll assess your situation and tell you exactly what we'd build — and what it would cost.

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