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Document Processing Engineering

Custom Intelligent Document Processing Pipelines

We build production OCR + computer vision + LLM extraction systems that turn messy, unstructured documents into clean, structured data. Fixed-fee. Deployed to your infrastructure. No per-page fees.

95-99%
Extraction Accuracy
85%
Manual Work Eliminated
3-4 wk
Build to Production
$0
Per-Page Fees
Start With a $500 Architecture Audit →
The Problem

Your documents are eating your operations.

Manual Data Entry

Staff spending hours re-keying data from PDFs, scans, and forms into your systems. Error-prone, expensive, and impossible to scale.

50 Document Formats

Invoices, purchase orders, medical forms, shipping docs — every vendor sends a different layout. No single template works.

Off-the-Shelf OCR Fails

Generic OCR tools choke on your specific document types. Poor accuracy on handwriting, stamps, low-quality scans, and multi-column layouts.

Compliance Demands Audit Trails

HIPAA, FDA, SOC 2 — regulators want to see exactly how data was extracted, verified, and who approved it. Manual processes leave gaps.

What We Process

Documents we turn into structured data.

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Invoices & POs

Line items, totals, vendor data

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Medical Forms

Prior auths, intake, EOBs

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Shipping Docs

Bills of lading, customs, POD

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QA Certificates

Inspection reports, COAs, SOPs

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Insurance Claims

Policy docs, adjuster reports

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Contracts & Legal

Key clauses, dates, parties

How It Works

4-layer extraction architecture.

Not just OCR. A multi-layer verification pipeline where each layer catches what the previous one missed.

Layer 1 — Barcode & QR Decode

Instant machine-readable data extraction. Barcodes, QR codes, Data Matrix — decoded first for high-confidence structured data.

Layer 2 — OCR Extraction

PaddleOCR PP-OCRv5 for text recognition. Handles multi-language, rotated text, low-DPI scans, and complex table layouts.

Layer 3 — Rules Engine

Business logic validation. Cross-references extracted fields against known formats, value ranges, and relational constraints. Flags anomalies automatically.

Layer 4 — LLM Verification

Gemini VLM visually inspects the original document against extracted data. Catches errors the previous layers missed. Human-in-the-loop for edge cases.

PythonFastAPIPaddleOCR PyTorchGemini VLMPostgreSQL DockerRailwayRedis
Build vs Buy

Why custom beats off-the-shelf.

Off-the-Shelf IDP Platforms

  • $2,000–$5,000/month subscription
  • Per-page fees add up fast
  • Limited to their document templates
  • Data leaves your infrastructure
  • Vendor lock-in on pricing and features
  • Generic accuracy on your specific docs
  • Compliance burden on third-party APIs

Custom IDP Pipeline

  • One-time build cost, you own the code
  • Zero per-page fees — unlimited processing
  • Built for your exact document types
  • Runs on your infrastructure
  • Modify and extend as needs evolve
  • 95-99% accuracy on your specific docs
  • Full audit trail and compliance control
The Starting Point

Before I write a line of code, I map the system.

Submit your document samples and workflow description. I'll analyze your extraction requirements and deliver a full technical blueprint — async, no calls required.

$500
flat · 3-day delivery
Credited toward any build engagement over $5,000.
Submit Your Project →

What you get: Document type analysis · extraction field mapping · accuracy feasibility assessment · architecture blueprint (OCR vs VLM vs hybrid) · infrastructure and deployment plan · integration design for your existing systems · Loom video walkthrough — all delivered async.

FAQ

Common questions.

What accuracy can I expect from a custom IDP pipeline?
Production pipelines typically achieve 95-99% extraction accuracy depending on document quality and type. Our 4-layer verification approach catches errors that single-method systems miss. Human-in-the-loop review handles the remaining edge cases so nothing ships with bad data.
How is this different from ABBYY, Rossum, or UiPath?
Those are platform products with per-page pricing and limited customization. A custom pipeline is purpose-built for your specific document types, runs on your infrastructure with no recurring per-page costs, and can be modified as your needs change. When off-the-shelf IDP is overkill or too rigid, custom wins.
How long does the build take?
A typical IDP pipeline ships in 3-4 weeks. Week 1: architecture and document analysis. Weeks 2-3: extraction pipeline development and testing. Week 4: integration with your systems, production deployment, and handoff with documentation.
Can the pipeline handle HIPAA or FDA compliance?
Yes. We build audit trails, role-based access controls, and data handling procedures that satisfy HIPAA, SOC 2, and FDA 21 CFR Part 11 requirements. All processing stays on your infrastructure — nothing leaves unless you explicitly configure it to.
What document formats do you support?
PDFs (native and scanned), images (JPEG, PNG, TIFF), Word documents, and email attachments. The pipeline handles rotated, skewed, multi-page, and low-quality scans through preprocessing, deskewing, and adaptive extraction strategies.
Can it integrate with our existing ERP or database?
Yes. The pipeline outputs structured JSON via a FastAPI endpoint. We build direct integrations with PostgreSQL, MySQL, REST APIs, webhooks, or any system that accepts data programmatically. If your ERP has an API, we connect to it.

Stop re-keying data. Automate it.

Submit your document samples and workflow description. I'll review everything async and deliver a full architecture blueprint within 3 days.

Submit Your Project →
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Start Architecture Audit →