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FinanceAI

ClaimsFast

Insurance, UAE

Key outcomeManual entry eliminated
83%
Reduction in processing time
0
Manual data entry required
99.1%
Extraction accuracy
The challenge

What needed
solving

A UAE insurance intermediary was processing 200–300 claims documents per week, with staff manually extracting policy numbers, claim types, damage descriptions, and supporting evidence from PDFs, scanned forms, and photos. A single claims processor was handling 40+ documents per day, with extraction errors creating downstream delays, compliance flags, and customer complaints about slow resolution times.

The solution

What we built

We built an AI document processing pipeline that ingests claims submissions from email, portal uploads, and WhatsApp. A vision-capable AI model reads each document — regardless of format — extracts the structured data fields, validates them against the policy database, flags incomplete or conflicting submissions, and routes clean claims to the correct team queue with a full data brief. Human review is only required for flagged exceptions, reducing total staff time per claim from 12 minutes to under 2 minutes.

Tech stack
GPT-4o VisionPythonAWS S3PostgreSQLn8nResend
Category
FinanceAI
Results

The numbers

Concrete, measurable outcomes delivered in production.

83%
Reduction in processing time
0
Manual data entry required
99.1%
Extraction accuracy
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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