Lettria - AI document intelligence for regulated industries

What is Lettria

In highly regulated industries such as healthcare, finance, legal, and engineering, organizations face a critical challenge: extracting reliable insights from complex, high-stakes documents while ensuring accuracy, traceability, and compliance. Traditional document processing methods struggle to handle the volume and complexity of clinical trials, financial disclosures, legal contracts, and technical specifications, often resulting in time-consuming manual review processes that cannot guarantee consistency or auditability.

Lettria is an enterprise-grade AI document intelligence platform designed specifically for regulated industries. Unlike conventional AI solutions that rely solely on vector-based retrieval, Lettria employs a proprietary GraphRAG technology that combines knowledge graphs with retrieval-augmented generation. This architectural approach transforms documents into verifiable knowledge graphs, where every answer can be traced back to its original source—eliminating AI hallucinations and ensuring regulatory compliance.

The platform's core differentiator lies in its commitment to verifiable, transparent AI outputs. When users query medical research, financial reports, or legal documents, Lettria provides answers that cite specific sources, enabling cross-referencing and audit trails essential for compliance-heavy environments.

Lettria serves prominent enterprises including La Poste, Total Energies, SIA Partners, Leroy Merlin, AP-HP (France's largest public hospital group), Euronext, Wisecube, and Alfa Laval. These organizations rely on Lettria to process thousands of documents monthly, extracting structured knowledge from unstructured content while maintaining the rigorous audit trails required in their respective industries.

Core Capabilities

Lettria offers a comprehensive suite of AI-powered features designed to transform how organizations process, analyze, and derive insights from documents. Each capability is engineered to address specific enterprise challenges while maintaining the transparency and verifiability that regulated industries demand.

Document Parsing serves as the foundational capability, extracting structured data from the most complex PDF documents. The parsing engine accurately identifies and extracts tables, charts, reading order, and multi-column layouts—preserving the contextual relationships within medical reports, financial statements, legal contracts, and engineering specifications. Organizations no longer need to sacrifice information density when digitizing their document archives.

Ontology Enrichment leverages AI to automatically generate domain-specific ontologies from documents, eliminating the need for manual mapping. This capability enables organizations to establish clean, consistent knowledge classification systems that evolve with their document corpus, supporting sophisticated knowledge management initiatives without requiring extensive ontology engineering expertise.

Text to Graph transforms arbitrary text into rich knowledge graphs containing entities, relationships, and constraints. This technology structures unstructured data at scale, creating interconnected knowledge bases that enable complex queries and relationship discovery across document collections.

GraphRAG represents Lettria's flagship innovation, combining graph-based retrieval with generative AI to produce transparent, explainable outputs. By leveraging knowledge graph traversal alongside traditional retrieval, GraphRAG achieves 30% higher accuracy compared to standard RAG implementations while eliminating the hallucination problems that plague conventional AI systems.

Additional capabilities include Private GPT for building and fine-tuning custom chatbots powered by proprietary data, Text Mining API for extracting insights from raw text data at scale, Text Classification API for categorizing content using domain ontologies, and Prompt Engineering services for optimizing AI outputs in vertical-specific applications.

Who Uses Lettria

Lettria's platform addresses the unique document intelligence needs across multiple regulated industries, with each sector benefiting from verified, traceable AI outputs that support compliance requirements and operational efficiency.

Healthcare and Life Sciences organizations leverage Lettria to query clinical trials, medical publications, and internal documentation. Medical and scientific teams can retrieve evidence-based insights with explicit source citations, accelerating evidence research by 60% while ensuring terminology consistency and regulatory compliance. AP-HP, France's largest public hospital group, utilizes Lettria's knowledge graph capabilities to structure patient data, while Theradial has transformed its operations through AI-driven data extraction.

Financial Services firms rely on Lettria for analyzing complex financial disclosure documents. The platform transforms lengthy financial reports into queryable knowledge bases, reducing complex data analysis from days to minutes. A leading banking group has deployed GraphRAG for high-precision ESG reporting, leveraging the platform's ability to trace every metric to source documents for auditor verification.

Legal Departments benefit from Lettria's ability to query regulations and contracts with source-level precision. Document cross-reference checking time is reduced by 40%, enabling legal teams to focus on strategic work rather than manual document review. The traceable outputs support litigation preparedness and regulatory compliance documentation.

Engineering Teams utilize Lettria to extract actionable insights from complex technical documentation. Problem resolution speed improves by 3x when engineers can query equipment manuals, specifications, and historical maintenance records with verifiable, step-by-step answers. Alfa Laval has achieved 20% accuracy improvement in technical document retrieval through GraphRAG implementation.

Customer Feedback Analysis at scale is enabled through NLP-powered text mining. SIA Partners processes 50,000 customer reviews daily using Lettria's text mining capabilities, extracting sentiment, themes, and actionable insights from unstructured feedback at enterprise scale.

Biomedical Research organizations benefit from Text to Graph technology for constructing domain-specific knowledge graphs. Wisecube has processed over 350,000 articles, achieving significant improvements in biomedical knowledge extraction accuracy and scalability.

Technical Capabilities

Lettria's technical architecture represents a significant advancement in enterprise AI, combining proprietary model development with robust integration capabilities designed for mission-critical deployments.

The Lettria Perseus proprietary model forms the foundation of the platform's intelligence. Trained specifically for knowledge graph generation tasks, Perseus achieves 30% higher accuracy than all other LLMs in graph generation tasks, with schema-validated graph generation completing in under 20ms. This performance enables real-time document processing at enterprise scale without sacrificing accuracy.

The Text to Graph Pipeline converts any text input into structured knowledge graphs containing entities, relationships, and constraints. Unlike simple entity extraction, this pipeline understands contextual relationships and semantic connections, creating knowledge representations that support complex analytical queries.

Document Parsing capabilities handle the most challenging document formats, including multi-column layouts, nested tables, charts with legends, and documents with non-linear reading orders. The parsing engine preserves the semantic structure of documents during digitization, ensuring that extracted data maintains its contextual meaning.

The GraphRAG architecture distinguishes Lettria from conventional RAG implementations. By combining graph-based retrieval with generative AI, the system maintains full transparency about how answers are constructed. Users can traverse the knowledge graph to understand exactly which documents and passages informed each response, eliminating the "black box" problem common in enterprise AI deployments.

Security and compliance are embedded throughout the architecture. The platform maintains full GDPR and CCPA compliance, with customer data stored exclusively on European servers ensuring data sovereignty. End-to-end encryption, regular security audits, penetration testing, and SSL/TLS connections protect data in transit and at rest. Lettria collaborates with ANSSI-certified consulting firms for independent data governance validation.

The platform provides comprehensive integration options through RESTful APIs and official GitHub SDKs. The perseus-client SDK simplifies model integration, while the t2g-sdk accelerates Text to Graph pipeline implementation. Documentation is available at docs.perseus.lettria.net, enabling technical teams to evaluate capabilities before committing to implementation.

Frequently Asked Questions