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HealthcareAIAutomation

MedRecord AI

Healthcare provider · Italy

Key outcomeDocument processing time cut by 80%
80%
Processing time reduction
97%
Extraction accuracy
500+
Documents processed per day
The challenge

What needed
solving

An Italian healthcare provider was manually processing 500+ patient intake forms, referral letters, and lab results per day. The administrative team was overwhelmed and document-to-system lag was causing delays in care coordination.

The solution

What we built

We built a GPT-4o Vision ingestion pipeline reading documents from a secure S3 bucket, extracting structured patient data, and pushing validated records to the EHR via n8n. Resend handles notification workflows for clinical staff.

Tech stack
GPT-4o VisionPythonAWS S3PostgreSQLn8nResend
Sector
Healthcare
Category
HealthcareAIAutomation
Results

The numbers

Concrete, measurable outcomes delivered in production.

80%
Processing time reduction
97%
Extraction accuracy
500+
Documents processed per day
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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