Our Services
Document Intelligence
Your archives are full of invoices, contracts, reports, and forms that no system can read. We turn them into structured, searchable data — automatically, accurately, and entirely on your infrastructure.
The problem
Your documents are locked in formats machines can't read.
Thousands of scanned contracts, invoices in PDF, handwritten forms, tables buried in Word documents. The information is there — but trapped behind layouts that basic OCR mangles and copy-paste destroys.
Your team spends hours manually extracting data from documents that should flow automatically into your systems. Every manual step introduces errors, delays processing, and doesn't scale.
You've tried off-the-shelf OCR tools. They work on clean, simple pages — and fail spectacularly on anything with tables, multi-column layouts, or mixed content.
How we fix it
From unreadable to structured — in four steps.
Audit your document landscape
We catalog your document types, formats, volumes, and quality. Scanned PDFs, handwritten forms, tables in Word — we find the hard cases before they find you.
Design the extraction pipeline
We select and configure the right combination of OCR engines, layout analysis models, and post-processing rules for your specific document types.
Build and benchmark
We process your documents, measure extraction accuracy against ground truth, and iterate until quality meets your acceptance threshold — field by field.
Deploy and automate
Production deployment with monitoring, error handling, and automated reprocessing. New documents flow through the pipeline without manual intervention.
What you get
Measurable results, not promises.
Mission report
"We went from three people manually typing invoice data to a fully automated pipeline — 10× faster, fewer errors."
Under the hood
Open-source document stack.
No black boxes. Every component is auditable, replaceable, and yours.
Docling
IBM's open-source document conversion engine — extracts text, tables, images, and structure from PDFs, DOCX, PPTX, and scanned documents with state-of-the-art accuracy.
Document Parsing
Hugging Face
We leverage state-of-the-art OCR and vision-language models from Hugging Face — including layout-aware transformers and multimodal LLMs — to extract text, tables, and structure from even the most challenging scanned documents.
SOTA OCR & Vision Language Models
DVC
Git-based version control for data and ML pipelines — track training data, model versions, and extraction benchmarks with full reproducibility.
Data Version ControlCommon questions about document intelligence.
How accurate is the extraction compared to manual data entry?
For clean, printed documents we typically hit 98%+ accuracy. For scanned documents with noise, skew, or mixed layouts, we achieve 95%+ after tuning. In both cases, we benchmark against your manually entered ground truth and only go live when accuracy meets your threshold.
Can it handle handwritten text?
Yes — with caveats. Modern OCR handles neat handwriting well, but messy handwriting remains a challenge industry-wide. We'll be honest about what's achievable for your specific use case and set up confidence scoring so low-certainty extractions get flagged for human review instead of silently failing.
What document formats do you support?
PDF (native and scanned), Word, Excel, PowerPoint, images (JPEG, PNG, TIFF), HTML, and plain text. Docling handles complex layouts including multi-column pages, nested tables, headers, footers, and embedded images. If your format isn't listed, chances are we can still process it.
How is this different from just using ChatGPT with document uploads?
ChatGPT processes documents one at a time, has size limits, and you can't verify what it extracted. Our pipeline processes thousands of documents automatically, extracts structured fields with measurable accuracy, and gives you traceable output — every extracted value links back to its source location in the original document.
What about GDPR and data privacy?
The entire pipeline runs on your infrastructure — no document ever leaves your network. There are no third-party API calls, no cloud OCR services, no data leaving EU soil. Every component is open source and auditable. Your documents stay yours.
How long does this take?
We start with a one-week proof of concept — we take a sample of your trickiest documents and deliver extracted, structured data so you can see the quality before committing. From there, we scale the pipeline to your full archive week by week, continuously improving accuracy and coverage as we encounter new document variations.
Let's unlock your documents.
30 minutes, no pitch deck. Bring your messiest document — we'll show you what structured extraction looks like.