Vedana

Vedana is a structure-first AI platform focused on transforming fragmented business knowledge from various document formats into structured data models. It addresses the challenge of organizational information scattered across files such as PDFs, Word documents, Excel sheets, shared drives, emails, wikis, and ERP exports, by extracting entities, attributes, and relationships to build a comprehensive knowledge graph. This approach enables AI to reason over the interconnected data, providing deterministic, rule-based answers rather than relying on similarity-based guesses.

The system creates a model of business knowledge by identifying anchors (entities), attributes (facts), and links (relations) from uploaded documents. For example, it can extract products, certificates, and suppliers from documents and map their relationships, such as which supplier provides a certified product for a specific market. Vedana’s AI then explores this structured knowledge using tools that query the model, compare options, and apply constraints step by step. The reasoning process is transparent, allowing users to trace the logic behind each answer and ensuring that results follow business-specific rules.

Vedana is designed for organizations seeking to unify and make sense of their distributed knowledge assets, with relevance for roles ranging from engineers and CFOs to clinicians, compliance officers, operations leads, and account managers. It supports a range of document types, including PDF, DOCX, and XLSX, reflecting the diverse sources of business information.

The platform is available as an open-core engine, with options for managed cloud deployment and enterprise support. This delivery model provides flexibility for businesses to choose between self-hosted and supported solutions according to their operational needs. Vedana’s focus on building structured knowledge graphs positions it within the class of AI tools that enable deterministic, rule-based reasoning over enterprise data.