Lettria

Freemium

A platform for text to create and deploy NLP projects without coding.

Lettria is a document intelligence platform designed for regulated industries to deploy NLP projects without coding. It features a Knowledge Studio for ontology enrichment, text-to-graph pipelines, and GraphRAG capabilities to improve data accuracy. The platform serves healthcare, finance, and legal professionals who need to build private GPT models and structured knowledge bases from raw text (verified: 2026-01-29).

Jan 29, 2026
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Pricing: Freemium
Last verified: Jan 29, 2026
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Key facts

Pricing

Freemium

Use cases

Data engineers in regulated industries building automated text-to-graph pipelines to convert raw text into structured GraphDB formats (verified: 2026-01-29), Healthcare organizations utilizing document parsing and text classification APIs to improve quality monitoring and CRM data enrichment (verified: 2026-01-29), Enterprise teams developing private GPT chatbots and fine-tuning models to maintain data security within a private environment (verified: 2026-01-29)

Strengths

The platform provides a Knowledge Studio that enables users to build and enrich ontologies directly from their own datasets (verified: 2026-01-29), Users can implement GraphRAG technology which combines graph databases and vector search to increase the accuracy of retrieval-augmented generation (verified: 2026-01-29), The system includes specialized document parsing and text classification APIs designed for high-stakes sectors like finance, legal, and healthcare (verified: 2026-01-29)

Limitations

Access to the platform and specific product guidance requires contacting the sales team as no self-service sign-up is visible (verified: 2026-01-29), Public pricing details are not disclosed on the website, necessitating a direct request for a demo to obtain cost information (verified: 2026-01-29)

Last verified

Jan 29, 2026

Strengths

  • The platform provides a Knowledge Studio that enables users to build and enrich ontologies directly from their own datasets (verified: 2026-01-29)
  • Users can implement GraphRAG technology which combines graph databases and vector search to increase the accuracy of retrieval-augmented generation (verified: 2026-01-29)
  • The system includes specialized document parsing and text classification APIs designed for high-stakes sectors like finance, legal, and healthcare (verified: 2026-01-29)

Limitations

  • Access to the platform and specific product guidance requires contacting the sales team as no self-service sign-up is visible (verified: 2026-01-29)
  • Public pricing details are not disclosed on the website, necessitating a direct request for a demo to obtain cost information (verified: 2026-01-29)

FAQ

How does Lettria assist organizations in improving the accuracy of their retrieval-augmented generation systems?

Lettria offers a GraphRAG solution that integrates graph databases with vector search capabilities. This combination is designed to increase RAG accuracy by approximately 30% through more structured data retrieval. The platform also provides a pilot program for organizations to test these improvements in their specific environments (verified: 2026-01-29).

What specific tools are available for users who need to build structured knowledge from unstructured text?

The platform features a Knowledge Studio and a Text to Graph pipeline. These tools allow users to build ontologies from their data and automate the creation of GraphDB structures from raw text. These capabilities are specifically tailored for document intelligence in regulated industries like finance and legal (verified: 2026-01-29).

Can developers integrate Lettria capabilities into their own software projects using standard programming tools?

Yes, Lettria provides API documentation and a software development kit (SDK) available via GitHub. This allows engineering teams to integrate text classification, document parsing, and ontology enrichment features directly into their existing workflows and CRM systems for better data accuracy (verified: 2026-01-29).