Extraction · invoices
Batch128 documents
FieldsSupplier · total · due
Checks2 flagged for review
Service
Data Extraction
PDFs, invoices, forms and web pages in. Clean, validated records out.
The problem
Critical data is locked inside documents and websites, and someone has to read and retype it by hand.
What it is
Data extraction uses vision models and OCR to read unstructured content and return structured records that match your exact schema.
How it works
Documents arrive by email or upload. A vision model extracts the fields you need against a strict schema, business rules validate the result, and anything uncertain goes to a quick human review.
How it runs
- Document received
- Fields read
- Checks applied
- Clean data delivered
OCR and vision
Read scans, photos and messy layouts precisely.
Schema enforcement
Every record matches your data model exactly.
Web capture
Navigate complex and login-gated sites to collect data.
Validation
Uncertain extractions are flagged for review.
Delivery
From first call to live system in four weeks.
- Week 1
Mapping
Identify document formats and the fields you need.
- Week 2
Tuning
Tune models to read your real-world layouts.
- Week 3
Integration
Deliver output to your ERP or database.
- Week 4
Accuracy
Refine on live samples until targets are met.
Outcomes
What it changes.
- Extraction accuracy
- 99%
- Faster processing
- 10x
- Saved versus manual entry
- Hours
Where it works
Invoice automation
Extract line items, tax and vendor details from inbound invoices straight into accounting.
Price tracking
Collect competitor pricing daily to inform your own pricing decisions.
Typical stack
- Vision models
- AWS Textract
- Puppeteer
- PostgreSQL
- Next.js
Security
Documents are processed in short-lived, isolated environments, then archived encrypted or deleted according to your retention rules.
Related work
In production.
FAQ
Questions, answered.
Yes. Modern vision models transcribe handwriting and messy scans reliably.