AI Document Extraction Pipeline
Turns messy PDFs and scans into clean, structured data automatically.
Overview
Turns messy PDFs and scans into clean, structured data automatically. I built a pipeline that OCRs incoming documents, uses OpenAI to extract the fields that matter into a structured schema, validates them, and pushes clean records into Airtable — flagging anything low-confidence for a quick human check. Built with OpenAI, Python, n8n, Airtable, this ai automation project was delivered for a client in USA and designed for reliability, a clean user experience and long-term maintainability — so it keeps delivering value well after launch.
The challenge
An operations team re-keyed data from invoices, contracts and forms by hand — slow, expensive and full of typos that caused downstream problems.
What I built
I built a pipeline that OCRs incoming documents, uses OpenAI to extract the fields that matter into a structured schema, validates them, and pushes clean records into Airtable — flagging anything low-confidence for a quick human check.
How I built it
- OCR'd incoming documents and extracted the key fields with OpenAI into a structured schema.
- Validated every extraction and flagged low-confidence results for a quick human check.
- Pushed clean, structured records straight into Airtable.
- Handled invoices, contracts and forms in a single pipeline.
Key features
- End-to-end workflow automation
- AI-powered steps for the smart work
- Error handling, retries and alerting
- Integrations with your existing tools
- Human-in-the-loop approvals where needed
- Full logging and an audit trail
The results
- Manual data entry all but eliminated
- Structured, validated data from any document format
- Low-confidence extractions flagged, not silently wrong
This is an example of my ai automation work. Need something similar? Start a project →
My delivery process
Discovery
We start by understanding the goal, the users and the constraints — no jargon, just a clear picture of what success looks like.
Plan & design
A clear scope, architecture and milestone plan, so you know exactly what's being built and when.
Build & iterate
Development in reviewable increments with regular updates, so you see working software early and often.
Launch & support
Testing, deployment and ongoing support, so it keeps running smoothly long after go-live.
AI Document Extraction Pipeline — FAQ
Can you build a ai document extraction pipeline for my business?
Yes. I build custom ai automation solutions like this ai document extraction pipeline, using OpenAI, Python, n8n, Airtable and tailored to your exact workflow, timeline and budget. Send me your requirements and I'll reply with a clear plan and quote.
How much does a project like this cost?
It depends on scope. After a short discovery call I provide a clear, fixed quote and milestone plan before any work begins — no surprises. Smaller builds start low; larger platforms are quoted per milestone.
How long does it take to build?
A focused MVP can take a few weeks, while a larger ai automation build runs in milestones over a couple of months. You'll see working software early and often, not just at the end.
What technology do you use, and will I own it?
This project uses OpenAI, Python, n8n, Airtable. I pick the right stack for each project, and you own 100% of the code and infrastructure — delivered in your own repositories and accounts.
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Want something like this built?
Tell me about your project and I'll get back to you within 24 hours. Prefer to chat? Message me on WhatsApp.