Doc Lexora classifies, organizes and understands your business documents with AI that runs entirely on your own infrastructure. No cloud APIs. No per-user fees. Your documents never leave your premises.
Doc Lexora integrates a local large language model through Ollama. Classification, search and document analysis run on servers you control — the intelligence of modern AI tools, without the cloud.
Every document that enters the system — uploaded, scanned from a watched inbox folder, or imported in bulk — is read and understood. The AI suggests title, document type, correspondent, tags, date and classification code.
Three layers of search work together on the same archive:
Doc Lexora parses documents with IBM Docling: headings, paragraphs, tables and images are extracted with their structure across PDF, Word, PowerPoint, Excel and HTML. Scanned documents go through multilingual OCR (Tesseract or local vision models).
This is the core architectural decision that defines Doc Lexora: every AI operation — language model, embeddings, vision OCR — runs on hardware you own. Document content is never transmitted to any third-party cloud service.
Personal data is never processed by external services. No data processing agreements with AI providers, no cross-border transfers, full data sovereignty and a complete audit trail of every access.
No external API calls, no risk of confidential content reaching third-party training data. Five-tier secrecy classification with per-user clearance keeps sensitive documents inside your security perimeter.
AI availability doesn't depend on a vendor's uptime. No per-query API costs that grow with usage, no vendor lock-in: model selection and configuration are fully in your hands.
Two-factor authentication (TOTP), customizable roles and permission matrices, five secrecy levels with user clearance, API keys for integrations, account lockout and IP logging.
Version history with comments and checksums, digital signatures (RSA, PDF embedding), retention policies with automatic enforcement, soft-delete with recovery, hierarchical cabinets with multi-filing.
State-machine workflow engine with configurable transitions, auto-trigger rules based on document properties, structured input fields at each step, full transition logging.
Reliable job queues for OCR, AI metadata, embeddings and knowledge-graph indexing. Watched inbox folders: drop files in, Doc Lexora processes them automatically. Scheduled maintenance built in.
Full interface in English, Italian and Finnish with locale-aware routing and dates. Multilingual OCR and AI metadata extraction across all three languages.
Complete audit trail of every operation, dashboards with document statistics and activity, backup and restore from the admin panel, and a REST API with 100+ endpoints for integrations.
Traditional enterprise DMS platforms rely on cloud-connected AI: your document content is processed on external infrastructure, at per-user prices that grow every year. Doc Lexora delivers comparable capabilities on your own servers.
| Capability | Doc Lexora | Traditional cloud DMS |
|---|---|---|
| AI document classification | Local LLM | Cloud AI |
| Conversational search with citations (RAG) | ✓ | ✗ |
| Semantic vector search | ✓ | Rare |
| Knowledge graph across the archive | ✓ | ✗ |
| Workflows, versioning, audit trail, signatures | ✓ | ✓ |
| 100% on-premise data | ✓ | Optional |
| 100% local AI processing | ✓ | ✗ |
| Per-user monthly licence fees | None | €40–90 /user/month |
Client confidentiality is non-negotiable. Secrecy classification, audit trails and local AI keep case files under your control — while conversational search saves hours of manual review.
High document volume meets automatic classification: invoices, contracts and reports are tagged and filed without manual effort. Retention policies keep you compliant.
The strictest GDPR requirements, five-tier classification, complete audit trails and data sovereignty — met by architecture, not by policy.
If you handle contracts, personnel files, financial records or client data, you get AI-powered document management without giving up privacy.
Doc Lexora installs on a dedicated server or virtual machine through a reproducible provisioning process. The application and its processing workers run as managed system services with automatic startup and recovery; containerized deployment is available as an alternative. Health-check endpoints, scheduled backups with rotation and automated maintenance are built in. Recommended hardware: 16+ GB RAM for AI workloads; GPU optional but recommended.
Request a personalized demo or a trial deployment on your own infrastructure. We'll show you what local AI can do with your documents — without your documents ever leaving your premises.
Request a demo