What is Vedana

Vedana is a system that makes AI outputs reliable and verifiable by grounding them in structured knowledge.

Vedana combines vector search, structured retrieval, and multi-step reasoning over data. The result is answers that are:

  • traceable — every reasoning step can be inspected and reproduced;
  • reproducible — the same question triggers the same operations;
  • aligned with real business logic — the assistant operates within an explicitly described data model.

Unlike typical RAG solutions, Vedana doesn’t rely on raw vector search or single-pass generation. It enables the AI to explore data step by step, following an explicit data model and a controlled reasoning process.

What this gives a company

  • Control over how answers are produced — not “LLM magic”, but an explicit playbook: which tool, in which order, for which kind of question.
  • Verify every reasoning step — which nodes and links were retrieved, which Cypher queries were executed, which document chunks contributed to the answer.
  • Reduce hallucinations — the answer relies on actual graph data, while the LLM acts as an interpreter, not a “source of truth”.

Where Vedana applies

Vedana is designed for domains where correctness is critical:

  • legal / compliance — which documents regulate a product category, which requirements apply to a contract;
  • e-commerce — product catalogs, compatibility, in-store stock, delivery policies;
  • internal knowledge bases — exact answers about documentation, regulations, organisational structure, processes;
  • B2B support — stable answers to typical client and partner questions.

What Vedana isn’t

  • It is not a replacement for classic RAG when it comes to summarization or vague “what is this document about?” questions — there, ordinary RAG is simpler and sufficient.
  • It is not a “smart” generative agent — Vedana deliberately constrains the LLM with an explicit set of tools so behaviour is predictable.
  • It is not a turn-key business product — you have to describe the data model and reasoning rules for your domain.

What’s next