Lettria is an AI-powered platform dedicated to transforming unstructured data into structured knowledge, thereby enabling smarter, context-rich decision-making. At its core is the "Graph Context Layer," which unifies structured data and unstructured knowledge through an ontology-driven graph, making enterprise AI actionable, traceable, and trustworthy.
In terms of use, Lettria is mainly aimed at scenarios that need to handle complex documents, scientific knowledge, and enterprise data, and is especially suitable for regulated industries. It offers two product paths: Knowledge Studio is a graph-native document intelligence platform for regulated industries, where GraphRAG can reason where vector RAG fails; Perseus is used to build production-grade graph agents on ready-to-use infrastructure.
Its main capabilities include three items: First, Ontology Building, which can automatically generate production-grade ontologies from domain data, quickly (days rather than months), with built-in governance and version control, and involving business experts; Second, Text-to-Graph, which can transform messy documents, tables, and SAP export data into clean, queryable knowledge graphs, unifying structured and unstructured data, with native support for tables, layout, and multimodality, and connecting existing data sources; Third, Graph Retrieval, where every answer can be traced back to its source, supporting multi-hop reasoning rather than keyword matching, and providing complete provenance for regulatory review.
In terms of usage, users can choose Knowledge Studio or use Perseus to start building. The platform supports generating ontologies from domain data, building and versioning knowledge graphs, and keeping business experts in the loop. For complex enterprise deployments, it also offers Forward Deployed services.
Applicable scenarios cover finance (structuring, validating, and querying financial, regulatory, and ESG information), healthcare (structuring medical, scientific, and pharmaceutical knowledge with traceable sources and accuracy), legal (navigating contracts, regulations, and complex legal documents, providing greater traceability in an evolving knowledge base), and engineering (transforming technical documentation into connected and usable enterprise knowledge, extracting from manuals, specifications, and complex industrial content).
In terms of limitations, the materials do not provide specific information such as pricing, platform support, deployment environment requirements, or usage thresholds.
