End-to-end document intelligence for complex industries
We build custom document pipelines that split, classify, extract, verify, stack, and answer questions across your entire document workflow. From scanned chaos to structured data.
Deep experience in document-heavy industries
We've built production document pipelines where accuracy and compliance aren't optional.
Mortgage
1003s, tax returns, pay stubs, loan tapes, disclosures, income verification, title docs
Insurance
Claims forms, policy documents, medical records, accident reports, agent submissions
Real Estate
Transaction packages, listing agreements, HOA docs, inspection reports, closing packages
Legal
Contracts, court filings, discovery documents, compliance records, signature extraction
We handle every step, not just OCR
Most "Document AI" stops at OCR. We build the complete workflow.
Split
Automatically separate multi-document PDFs into individual documents. Detect page boundaries, identify document starts, handle stapled and merged files.
Classify
Identify document types across hundreds of variations. Same form, different year, different state, different organization—we handle it.
Extract
Pull key fields into structured data your systems can use. Forms, tables, handwriting, checkboxes, signatures—all mapped to your schema.
Verify
Cross-check extracted values against business rules and source documents. Flag inconsistencies, calculate confidence scores, route exceptions.
Stack
Organize documents into the required order for downstream systems. Build compliant loan packages, assemble case files, prepare for audit.
Q&A
Answer questions across your document corpus. "What's the income on this application?" "Are all required documents present?" "Does this match the disclosure?"
OCR gives you text. It doesn't deliver structure, field mapping, classification, or verification under messy real-world conditions.
Without evaluation criteria and production testing, you can't know where it fails or whether it's safe to deploy at scale.
We handle the document chaos you actually have
Not clean PDFs from your vendor demo. The messy reality that shows up in production.
Document Sources
- Mobile phone photos (skewed, shadowed, low-res)
- Scanned PDFs with compression artifacts
- Electronic documents (native PDFs, Word)
- Mixed packets with all of the above
Optical Challenges
- Rotation (90°, 180°, arbitrary angles)
- Skew and perspective distortion
- Noise, speckle, and scan artifacts
- Handwriting over printed text
Structural Challenges
- Complex tables and nested layouts
- Multi-page forms with page breaks
- Inconsistent versions (by year/state/org)
- Merged documents without clear boundaries
Custom models for your toughest cases
When off-the-shelf doesn't cut it, we build what you need.
Fine-Tuned Foundation Models
We fine-tune vision and language models on your specific document types. Get dramatically better accuracy on your exact use cases without starting from scratch.
Custom Classification Models
When you have hundreds of document types and generic classifiers fail, we train models on your taxonomy. Fast, accurate, and tuned for your edge cases.
Domain-Specific Extractors
Extractors trained to understand your industry's vocabulary, form layouts, and data patterns. Not generic NER—purpose-built for mortgage, insurance, legal, or real estate.
Document Q&A Systems
Ask questions in natural language across your document corpus. Built with retrieval-augmented generation and citation back to source documents.
What we ship
Not a demo that dies after a week. A production pipeline your team can run and own.
Deployment options
We meet you where your infrastructure is.
See extraction in action
Upload a document and watch structured data appear.
Our demo shows field extraction, checkboxes, signatures, and tables—a sample of what our full pipeline delivers. For privacy and cost control, the demo processes one page at a time.
Try the extraction demo →Let's talk about your documents
Book a discovery call and we'll discuss:
- Your document types and current pain points
- Whether automation is a fit (and where it isn't)
- What "done" looks like for your workflow
- Timeline and investment for a production solution