Lettria
A document intelligence platform targeting regulated industries such as finance, healthcare, and law, the official stated that it replaces vector retrieval with knowledge graphs, providing document parsing, ontology construction and graph retrieval, with traceability as its core feature.
Updated: 2026-10-26
What is Lettria?
The official Lettria website positions itself as "Document AI for Regulated Industries" and proposes the "Graph Context Layer": unifying structured data and document knowledge into an ontology-driven graph, enabling enterprise AI responses to be traceable and auditable. Its product line is divided into two entry points: Knowledge Studio for knowledge and business teams, and Perseus for developers and technical teams. The website also lists four industries—finance, healthcare, law, and engineering—along with the Forward Deployed option for complex deployments.
Who is it for?
- Knowledge management and document processing teams in highly regulated industries such as finance, healthcare, law, and engineering.
- Engineers within enterprises who are working on retrieval-augmented generation but whose recall quality has been stuck by vector solutions.
- Business departments that need to extract structured fields from contracts and reports and leave audit trails.
- Want business experts to participate in ontology design, rather than leaving the entire task to algorithm-focused data teams.
Key features
6Knowledge Studio
Officially described as a graph-native document intelligence platform for regulated industries, it focuses on "where vector search fails, graphs can still reason", with a claimed accuracy improvement of over 30% on the official website, and emphasizes compliance and traceability.
Perseus
Targeted at developers and technical teams, the official claims it can build ontologies and knowledge graphs in minutes rather than months, supports version management for graphs, and enables business experts to participate in the process.
Document Parsing
Document parsing converts raw documents into retrievable and queryable structured content.
Ontology Enrichment
Ontology enrichment, which uses domain ontologies to add semantic relationships to parsed results.
Text-to-Graph
Text-to-Graph, the official website also provides a public Text-to-Graph leaderboard and document center.
Graph Retrieval
Graph Retrieval, the official website emphasizes three features: multi-hop reasoning, unification of structured and unstructured data, traceability and auditability.
How to use Lettria
- First clarify the types of questions you need to answer before defining the ontology scope.
- an overly broad ontology will lead to a rapid rise in upfront costs.
- The 30%+ accuracy improvement stated on the official website comes from the company's own description.
- It is recommended to conduct a comparative test with your own document set before implementation.
- For complex enterprise implementations, you can opt for the Forward Deployed option listed on the official website, with the official team assisting with the deployment.
- When dealing with sensitive data such as patient and customer information, first confirm the deployment methods and data processing terms.
- The official website provides a security page and enterprise version descriptions.
- The official website also provides a Text-to-Graph leaderboard, white papers, and a glossary.
- you can read these documents first during the selection phase.
- Pricing and features are subject to change.
- verify the pricing and descriptions on the official website before commercial use.
Traffic & popularity
Data month Sep 2026
Lettria receives about 12.8K visits per month and ranks #1,506,214 worldwide.
Monthly visits
12 monthsTraffic sources
- Direct39.9%
- Search34.0%
- Referrals10.1%
- Social6.2%
- Mail3.1%
- Other6.7%
Top countries
- France32.4%
- United States28.9%
- India18.0%
- Brazil12.1%
- Pakistan8.6%
Estimated from third-party traffic data.
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