Vrin is an AI deep-search and action engine for company data. Vrin unifies siloed data from company’s SaaS stack (Jira, Confluence, Google Workspace, Slack, etc.) into an entity-centric knowledge graph and leverages HybridRAG with multi-hop reasoning to produce permission-aware, evidence-backed facts & insights, securely inside company’s private cloud. Imagine having a super intelligent companion at work that knows everything about you, your company & how you work.
As Andrew Ng said it best, "Focusing on the quality and structure of data fueling AI systems is what unlocks its power." That's exactly what Vrin is optimizing for – structuring the data in the best way possible that facilitates multi-hop reasoning and cross-document synthesis unlike traditional RAG systems which leverages an extremely naive approach by simply trying to retrieve context through keyword matching. Everyone's stuck optimizing reasoning-chains & chain-of-thought at query time but none of that can help the retriever if the data is not structured efficiently and in an intelligent manner.
Additional Research Avenues and Market Differentiation: Most enterprise AI tools focus on minimizing hallucinations to safely answer “what does the data say?” but that caps their ability to help companies think in new ways. Vrin also answers “How would our best people think about this, and what new approaches are we missing?”, using a dedicated brainstorming/strategy model that channels LLM creativity into domain-specific ideas, then runs every suggestion back through the company’s knowledge graph to tag what’s grounded, what’s plausible but unverified, and what’s likely impossible. This “controlled cognitive core” positions Vrin as an AI-first strategy lab for each customer: safe and evidence-aware, but capable of surfacing novel approaches their competitors will never see.
