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Lettria

Lettria

The graph context layer that turns complex enterprise knowledge into reliable, traceable AI answers.

softwareAI Research & AnalysisGraphRAGKnowledge GraphsEnterprise AI

What is Lettria?

Lettria is an enterprise AI platform built around a Graph Context Layer for regulated industries. It unifies structured data and unstructured knowledge into ontology-powered knowledge graphs, giving AI systems a grounded, traceable and trusted context to reason over. Instead of relying on vector search alone, Lettria combines GraphRAG, graph-native document intelligence and production-grade graph agents to deliver answers that can be inspected, verified and defended in compliance-heavy environments. Lettria addresses the limits of vector retrieval: where standard RAG struggles to connect multiple sources, handle structured business data or explain its answers, Lettria's graph approach supports multi-hop reasoning, numerical and temporal reasoning, and full provenance on every response. The platform converts messy documents, tables and SAP exports into queryable knowledge graphs with auto-generated, version-controlled ontologies - built in days, not months, with business experts kept in the loop. Benchmarks show a 30%+ accuracy improvement, up to 400× faster processing than general LLMs, and 81.7% overall accuracy in published evaluations. Lettria offers two entry paths: Knowledge Studio, a graph-native document intelligence platform for knowledge and business teams, and Perseus, an infrastructure for developers building production-grade graph agents. The platform serves finance, healthcare, legal and engineering organizations, with customers including Alfa Laval, WiseCube and Imago Platform. For complex knowledge problems, Lettria also provides forward-deployed engineers, ontology experts and applied AI specialists to take projects from prototype to production.

SpecificationsAI-estimated

ProductGraph Context Layer for Enterprise AI
Main productsKnowledge Studio, Perseus
Target sectorsFinance, Healthcare, Legal, Engineering
Core capabilitiesOntology Building, Text-to-Graph, Graph Retrieval
Speed improvementUp to 400× faster than general LLMs
Customer referencesAlfa Laval, WiseCube, Imago Platform
Accuracy improvement30%+ better than vector RAG
Overall reasoning accuracy81.7%
Temporal reasoning accuracy83%
Multi-hop reasoning accuracy90%+
Numerical reasoning accuracy100%

Key Features of Lettria

GraphRAG-powered retrieval turns complex enterprise knowledge into reliable, traceable answers
Knowledge Studio provides graph-native document intelligence built for regulated industries
Perseus lets developers build production-grade graph agents on ready-to-use infrastructure
Auto-generates production-grade ontologies in days, not months, with governance and version control
Text-to-Graph converts messy documents, tables and SAP exports into clean, queryable knowledge graphs
Unifies structured and unstructured data, including native tables, layouts and multimodal content
Graph retrieval delivers multi-hop reasoning instead of keyword matching, with zero hallucinations by design
Every answer includes full provenance, making AI audit-ready for regulatory review
Benchmark-backed performance: 30%+ more accurate, up to 400× faster, 81.7% overall accuracy

Use Cases for Lettria

1

Regulated document intelligence

Turn complex financial, legal or medical documents into traceable knowledge that teams can query with confidence.

2

Financial and ESG reporting

Structure regulatory and ESG information so answers can be verified and audited in demanding finance environments.

3

Healthcare knowledge management

Organize medical, scientific and pharmaceutical knowledge with traceable sources and high accuracy.

4

Legal contract navigation

Search contracts, regulations and complex legal documents with multi-hop traceability across evolving knowledge bases.

5

Engineering technical documentation

Convert manuals, specs and complex industrial content into connected and usable enterprise knowledge.

6

Production-grade graph agents

Build and deploy graph agents for enterprise workflows using Perseus on ready-to-use infrastructure.

7

Replacing vector RAG

Overcome vector search limits when AI must connect multiple sources and answer questions that require reasoning.

8

Ontology generation and governance

Auto-generate, version and govern ontologies from domain data with business experts in the loop.

How to use Lettria?

1

Choose your entry path

Select Knowledge Studio for business and knowledge teams or Perseus for developer-led graph-agent projects.

2

Connect and load your sources

Bring in documents, tables, SAP exports and other structured or unstructured enterprise data.

3

Build or refine the ontology

Auto-generate an ontology from your domain with Lettria, then iterate with business experts to capture your domain's real logic.

4

Transform data into a knowledge graph

Use Text-to-Graph to unify your sources into a clean, queryable graph infrastructure.

5

Query with GraphRAG and verify

Ask questions through the platform or agents, then inspect provenance and trace every answer back to its source.

Pros & Cons of Lettria

Pros

  • Ontology-powered GraphRAG delivers 30%+ better accuracy than vector RAG
  • Every answer traces back to its source, making AI audit-ready for regulatory review
  • Unifies structured and unstructured data, including documents, tables and SAP exports
  • Auto-generates governed, version-controlled ontologies in days, not months
  • Benchmark-backed performance: up to 400× faster and 81.7% overall reasoning accuracy

Cons

  • No pricing or free tier is listed on the site, suggesting an enterprise-focused commercial model
  • May be overkill for teams with simple retrieval needs where vector search is sufficient
  • Requires resourceful team alignment to integrate the graph layer into existing enterprise workflows
  • Self-serve onboarding may be steep for non-technical business teams without expert support

Frequently Asked Questions

What is Lettria?

Lettria is an enterprise AI platform that unifies structured and unstructured knowledge into ontology-powered graphs to make AI grounded, traceable and trusted.

What is GraphRAG?

GraphRAG is Lettria's approach to retrieval-augmented generation that uses knowledge graphs and multi-hop reasoning instead of simple vector matching.

How is Lettria different from vector RAG?

Vector RAG is effective for simple retrieval but limited when connecting multiple sources or handling structured business data. Lettria's graph agents achieve higher accuracy in multi-hop, numerical and temporal reasoning.

What are Knowledge Studio and Perseus?

Knowledge Studio is a graph-native document intelligence platform for business teams, while Perseus is developer infrastructure for building production-grade graph agents.

Does Lettria require hand-built ontologies?

No. Lettria auto-generates ontologies from your domain data in days, not months, and keeps them governed and version-controlled with business experts in the loop.

How does Lettria ensure traceability?

Every answer is backed by full provenance tracing back to source data, making outputs ready for regulatory review and audit.

Which industries does Lettria serve?

Lettria is built for complex and regulated industries including finance, healthcare, legal and engineering.

What performance results has Lettria published?

Lettria reports 30%+ better accuracy, up to 400× faster processing than general LLMs, and 81.7% overall reasoning accuracy in published evaluations.

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Target AudienceEnterprise

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Tags

GraphRAGKnowledge GraphsEnterprise AIDocument IntelligenceOntologyTraceability

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