Lettria
Lettria is a platform that empowers organizations to enhance AI applications through graph-based technologies, focusing on knowledge graphs and automated text analysis.
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Description
Lettria is a comprehensive platform designed to enhance artificial intelligence applications by utilizing graph-based technologies. At its core is the GraphRAG feature, which combines knowledge graphs with retrieval-augmented generation (RAG) technology to improve the accuracy and contextual relevance of responses generated by large language models (LLMs). This hybrid solution addresses data hallucination issues effectively by transforming unstructured text into structured knowledge graphs through processes such as document parsing, entity recognition, vector management, and database merging.
The platform provides a range of functionalities tailored for organizations looking to manage and analyze data efficiently. Key features include Ontology Enrichment, which allows users to build and manage ontologies, and a Text to Graph Pipeline, enabling the seamless integration of text data into knowledge graphs. Lettria offers several APIs for text classification, cleaning, and mining, which are essential for organizations aiming to extract insights from raw text data.
Lettria has demonstrated its capabilities through successful use cases with clients like AP-HP, which utilizes the platform for structuring patient data, and Leroy Merlin, which leverages knowledge graphs for product recommendations. By enabling precise and insightful answers to complex questions, Lettria enhances the reliability of generative AI applications while maintaining quality and explainability.
Organizations can automate routine tasks with Lettria’s tools, significantly minimizing AI errors and fostering collaboration across teams. The platform is positioned to unlock deeper knowledge through advanced AI techniques, making it an essential tool for enterprises focused on knowledge management and innovation.
Features
GraphRAG Feature
An innovative approach combining knowledge graphs with retrieval-augmented generation technology to improve response accuracy and contextual relevance in AI applications.
Ontology Enrichment
Tools for building and managing ontologies, allowing users to create structured knowledge frameworks tailored to their data needs.
Text to Graph Pipeline
Facilitates transforming unstructured text data into structured knowledge graphs for better data analysis and insight extraction.
Data Integration APIs
APIs for text classification, cleaning, and mining, designed to streamline the integration of diverse data sources and enhance data quality.
Tags
Documentation & Support
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- Online Support
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