Knowledge locked in scans
Critical information lives in scanned PDFs and images that no search engine or language model can read.
Document AI & Anonymization
Document AI, OCR and PII anonymization
We build document AI pipelines that read scanned PDFs, forms and records, extract structured data, and remove personal information before anything is published, indexed or sent to a model. Our anonymization engine for court decisions reached 98% detection accuracy with 100% data-protection and OHADA compliance.
What you can expect
- 98% PII detection on multi-jurisdiction legal data
- 100% data-protection and OHADA compliance
- Scanned archives converted into RAG-ready JSON
(01) The problem
Why teams come to us for Document AI & Anonymization.
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Personal data blocks publication
Court decisions, medical records and contracts can't be shared or indexed until names, addresses and identifiers are removed.
Rules differ by jurisdiction
What must be redacted, and how, changes between countries and legal systems.
Manual redaction doesn't scale
Human review is slow, expensive and inconsistent across tens of thousands of documents.
(02) Use cases
What we build with Document AI & Anonymization.
- 01
Court-decision anonymization
Detect and pseudonymize parties, witnesses and identifiers, with stricter safeguards for minors and vulnerable people.
- 02
OCR-to-RAG pipelines
Five-stage pipelines (PDF, image, preprocessing, OCR, structuring) that produce vector-ready JSON.
- 03
Contract and form extraction
Pull parties, dates, amounts and clauses into structured fields your systems can use.
- 04
Data preparation for AI
Restructure large CSV and SQL datasets into clean, RAG-ready knowledge, as we did for an investment database.
- 05
Medical and financial records
Extraction and de-identification for sensitive records under strict privacy requirements.
- 06
Classification and routing
Classify incoming documents and route them to the right team or workflow automatically.
Deliverables
Everything you need to run it in production.
- OCR and layout-aware parsing pipeline
- Entity extraction with structured JSON output
- Multi-jurisdiction PII detection and anonymization engine
- Rule packs per jurisdiction and document type
- Human review queue for low-confidence detections
- Accuracy evaluation and compliance reporting
- Integration with search, RAG and storage systems
Our approach
How we deliver reliable results.
- 1
Define the compliance target
We translate the legal and regulatory requirements of each jurisdiction into redaction rules we can test.
- 2
Layer detection methods
Pattern rules, named-entity recognition and LLM reasoning work together, so one method's blind spot is covered by another.
- 3
Protect the most vulnerable first
Minors and vulnerable parties get stricter rules and dedicated checks.
- 4
Measure, then automate
Detection accuracy is measured on labelled samples before automation is trusted at scale.
- 5
Keep people in the loop
Low-confidence detections go to reviewers instead of slipping through silently.
Proof
Related case studies, with real numbers.
Legal-techProduction platform
Datagreffe Justice
An enterprise legal AI platform for 50,000+ court decisions
- court decisions indexed
- 50,000+
- court decisions indexed
- PII detection accuracy
- 98%
- PII detection accuracy
- data-protection & OHADA compliance
- 100%
- data-protection & OHADA compliance
Document AI
Enterprise OCR-to-RAG Pipeline
A five-stage pipeline that turns scanned archives into search-ready knowledge
- pipeline stages
- 5
- pipeline stages
- in
- Scanned PDF
- in
- out
- Vector JSON
- out
Finance & investment
Multi-Agent Financial Document Intelligence
Specialized AI agents that turn earnings calls and financial PDFs into client-ready reports
- specialized CrewAI roles
- Multi-agent
- specialized CrewAI roles
- transcript to report
- End to end
- transcript to report
- structured output
- Client-ready
- structured output
Also delivered
- Cleaning and structuring of a large-scale CSV and MySQL investment database into RAG-ready data
Technology
Tools we use for Document AI & Anonymization.
Model-agnostic and cloud-agnostic: we pick the right components for your data, budget and compliance requirements.
- Claude
- OpenAI
- spaCy
- Microsoft Presidio
- Tesseract OCR
- AWS Textract
- Azure Document Intelligence
- Unstructured
- PyMuPDF
- Elasticsearch
- Python
- Flask
Industries we serve
Engagement models
Flexible ways to work, one standard of delivery.
Start small with a discovery sprint or an audit, or go straight to a production build. Most projects start from $5,000, scoped after a free strategy call.
1–2 weeks · fixed scope
AI Strategy & Discovery Sprint
Teams validating an AI opportunity before committing a budget.
- Use-case and ROI workshop
- Data and systems audit
- Architecture blueprint
- Risk and compliance review
- Build plan with estimates
4–12 weeks · milestone-based
Production Build
A defined RAG platform, AI agent, automation or AI product, delivered end to end.
- Architecture and full build
- Evaluation suite and QA
- Security and compliance controls
- Deployment and monitoring
- Documentation and handover
Monthly retainer
Dedicated AI Engineering
Product and platform teams with an ongoing AI roadmap and no time to hire.
- Senior AI engineering capacity
- Weekly planning and demos
- Continuous evaluation and monitoring
- Model and cost optimization
- Scale up with vetted specialists
1–3 weeks · fixed scope
AI Audit & Evaluation
An existing LLM, RAG or agent system that underperforms or is changing hands.
- Architecture and code review
- Answer-quality evaluation
- Security, PII and compliance review
- Cost and latency analysis
- Prioritized remediation report
Not sure which model fits? A free 30-minute call is enough to decide.
Book a free strategy callDocument AI & Anonymization FAQ
Common questions about Document AI & Anonymization.
Can't find your answer? Ask us on a free strategy call or send a short brief.
What is intelligent document processing?
It combines OCR, layout understanding, machine learning and LLMs to read documents the way a person would, then outputs structured data your systems can search, analyze and automate.
How accurate is your PII anonymization?
Our multi-jurisdiction engine for court decisions reached 98% detection accuracy, and the platform met 100% of its data-protection and OHADA compliance requirements. We measure accuracy on labelled samples of your own documents.
Which personal data can you detect?
Names, addresses, ID and passport numbers, phone numbers, emails, bank and financial details, dates of birth, case-specific identifiers and any custom entities you define.
Do you support languages other than English?
Yes. We have shipped French-language legal anonymization and retrieval, and our pipelines support multilingual extraction.
Can documents stay on our own servers?
Yes. OCR, detection and open-weight models can run inside your cloud or on-premise, so documents never leave your environment.
What happens to uncertain detections?
They are routed to a human review queue with the context needed to decide quickly, so automation never silently guesses.
Taking on new projects
Let’sbuild.
Have an AI project in mind? Let’s make it real.
Book a free 30-minute strategy call with our founder. You’ll leave with a clear view of the right architecture, timeline and next step, whether or not we work together.
- Reply within 24 hours
- NDA before you share anything confidential
- You own the code, prompts and documentation
- Hours overlap with US, UK, EU and Gulf teams