Increase your RAG accuracy by 30% by joining Lettria's Pilot Program. Request your demo here.

AI that understands your document
and delivers verified knowledge

Extract reliable insights from complex, high-risk documents with full traceability.

5 stars

Trusted by leading teams processing thousands of documents every month.

How Lettria solves the
RAG problem across industries

Traditional RAG fails on complex documents. Lettria delivers reliable, traceable intelligence.

Most RAGs lose structure with tables, diagrams, or multi-column layouts.

Lettria’s graph-based, layout-aware parsing keeps every element intact, preserving relationships and context so complex documents become fully accurate, queryable data sources.

Keyword search can’t handle multi-step, conditional numerical questions.

GraphRAG builds a semantic map of your knowledge, enabling reasoning across documents, applying constraints, and delivering answers that truly support decision-making.

Without structure, agents hallucinate and fail at complex workflows.

Lettria’s dynamic knowledge graph grounds agents in facts, enabling step-by-step reasoning, traceable decisions, and reliable execution in high-stakes environments.

From complex documents to actionable insights

Lettria’s four core modules work together to extract structure, build knowledge, and deliver fully traceable outputs, grounded in your own data.

Document Parsing

Extracts tables, diagrams, reading order, and multi-column layouts from the most complex PDFs.


View Document Parsing

Ontology Building

Automatically generates clean, domain-specific ontologies from your documents, no manual mapping required.


See Ontology Building

Text to Graph

Converts any text into a rich knowledge graph with entities, relations, and constraints.


Explore Text to Graph

GraphRAG

Combines graph retrieval with reasoning for transparent, interpretable outputs without hallucinations.

Learn about GraphRAG

Trusted by leading teams

How leading teams boost accuracy, automation, and scalability with Lettria.

10,000+
new classes added

Automated ontology enrichment at scale.

“Lettria accelerated our enrichment process and improved recommendation accuracy.”

350,000+
articles processed

Scalable extraction for biomedical research.

“Lettria accelerated our enrichment process a“Lettria significantly improved the accuracy and scalability of our biomedical knowledge extraction.”nd improved recommendation accuracy.”

+20%
better accuracy

Faster, more accurate outcomes using GraphRAG.

“Lettria helped our experts avoid repetitive document analysis and deliver faster, more accurate results.”

Helping analysts cracking big issues in every industry

From clinical trials to compliance, GraphRAG extracts insight from complex data and documents, powering safe, fast, and evidence-based decisions.

See case study

Extract and structure financial data to speed up audit, risk, and compliance workflows.

See case study

Accelerate contract review and compliance by detecting key clauses and obligations.

See case study

Turn technical documents into queryable graphs for faster development and QA.

See case study

Meet Lettria Perseus, our new model.

Lettria Perseus, where precision meets speed: 30% more accurate than any other LLMs on graph generation, schema-valid graphs under 20 ms. Build trustworthy graph-AI at enterprise scale.

Work with our experts to build your knowledge layer.

Lettria combines expert support and proven methods to accelerate results, reduce risk and unlock analyst-level intelligence.

Week 1-4

Connect Your Data

 Defining project needs, stakeholders, and success metrics

 Collecting your relevant documents and sources

 Parsing unstructured data and structuring it

 Designing your first ontology and knowledge graph with our experts.

Weeks 5-8

Activate Insights

 Prototype development & testing

 Feedback loops using evaluation matrix

 Continuing enriching ontology, improving relationships in the graph

Weeks 9-12

Monitor & Improve

 Final iteration completed, preparing the system for deployment

 Integration into your information systems, production of API docs

 Final result: A verifiable, trustworthy AI

Build trustworthy, domain-grounded intelligence

Improve RAG accuracy by 30% and let your documents deliver precise, explainable results.