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PARSING PROOF
Unstructured was the hard problem.
We solved it first
Technical drawings, tables and annotations are parsed into structured fields, entities and relationships.
GraphRAG - document intelligence for complex enterprise knowledge
Complex documents.
Complex questions.
One layer that handles both.
GraphRAG parses what other systems can't, then reasons over it in ways vector search was never built for.
Trusted by teams turning complex knowledge into reliable AI.
CASE STUDIES
Already in production in regulated industries
Lettria structures complex documentation, scientific knowledge and enterprise data into AI systems that are reliable, traceable and usable in production.
DOCUMENT INTELLIGENCe
Why your questions get the wrong answers
A 400-page filing where the number you need sits in a table on page 47 and its definition is in an annex. A drawing where the tolerance lives in the callout, not the text. A contract where clause 12 has been superseded twice, and only the appendix says so. This is the normal use case in your work, and the edge case in most systems.
multimodal · millions of pages · Different types of files
Your documents break parsing
Tables, figures, scanned annexes, mixed layouts. Most systems assume clean prose and quietly drop what they can't read figures, tables and annexes. Everything in the input is wrong or misunderstood.
multi-hop · numerical · temporal
Your questions break retrieval
You're rarely asking what a document says. You're asking what follows from four of them. Which obligations changed when this amendment landed. Whether figures spread across nine reports breach a threshold. Whether a design still complies given a revision published after it shipped.
Built for the experts who can't afford a wrong answer
Regulated industries don't just have complex documents. They have questions that chain facts across sources, where every answer has to trace back to where it came from.
Financial services & compliance
Regulatory obligation tracking
Base regulation → each amendment → your internal policy: every hop in that chain carries its source, so the whole path is auditable.
PharmaCEUTICAL & healthcare
Drug safety and literature cross-referencing
Does this adverse event pattern connect to prior trial data, a compound interaction, something already in the literature? The answer gets assembled across trial reports, lab results, and papers with tables and figures included, and every piece traces back to its source.
Manufacturing & energy
Technical standard compliance
Does this component design comply with the current standard? Design → standard → revision history → incident precedent, with a verifiable source on every link.
BENCHMARK
Where vectors break, graphs reason
Have a look at the full GraphRAG vs Vector RAG comparison table across multi-hop, numerical, temporal, overall accuracy
Capability
Vector Agents
Graph Agents · Lettria
Multi-hop reasoning
Low
90%+
Numerical reasoning
Low
100%
Temporal reasoning
50%
83
Overall accuracy
57.5%
81.7%
Stop guessing which answers to trust.
