Introduction

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Why Vrin

• Extracts structured facts (entities, relationships, timestamps) from every document
• Traverses entity connections to answer questions that span dozens of documents
• Reasons across your knowledge graph to assemble precisely the context your LLM needs
• Traces every answer to specific facts from specific source documents

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Key features

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How it works

1. Structure — VRIN extracts entities from your query and traverses the knowledge graph to find relevant facts, relationships, and temporal context.
2. Reason — Graph facts and document chunks are intelligently fused, scored for confidence, and assembled into precisely the context your LLM needs.
3. Trace — Every answer includes the specific facts used, the source documents they came from, and confidence scores — so you can verify every claim.

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For AI Agent Builders

from vrin import VRINClient

client = VRINClient(api_key="vrin_your_api_key")
result = client.query("What changed in ACME's revenue between Q2 and Q3?")

# Every answer traces to specific facts
for source in result.get("sources", []):
    print(f"  {source['document']}: {source['fact']}")

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Benchmarks

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Next steps