Deasy Labs

Deasy Labs automates the transformation of unstructured data into structured, AI-ready knowledge bases. It continuously curates data by tagging, filtering, and enriching content, ensuring that AI systems have access to fresh and relevant information. This process enhances data retrieval and prevents knowledge decay.

Deasy Labs utilizes a context engine that leverages AI and machine learning models to automate data curation. It employs advanced algorithms for tagging, filtering, and enriching unstructured data, ensuring high accuracy and relevance in knowledge bases.

Key features of Deasy Labs include automated content discovery, domain-specific taxonomy generation, 90%+ classification accuracy, and continuous knowledge base maintenance. It also provides sensitive data detection and contextual metadata enrichment for improved data retrieval.

Deasy Labs employs a combination of AI and machine learning models to optimize data tagging and classification processes. This approach allows for efficient token use and enhances the accuracy of knowledge retrieval without relying heavily on domain experts.