VrinVRiN
The Vrin blog

Engineering & research.

Deep dives into knowledge reasoning architecture, benchmark results, and the technology powering enterprise AI.

Featured

Karpathy Is Right About LLM Knowledge Bases. Here's What Happens When You Stress-Test the Idea.

We ran the same strategic question through two workflows: a local filesystem agent reading files directly vs Vrin's graph-aware retrieval. Same AI, same documents, same question. Here's what we found.

April 9, 202610 min read
Read article
All articles7 posts
karpathyknowledge-bases

Karpathy Is Right About LLM Knowledge Bases. Here's What Happens When You Stress-Test the Idea.

We ran the same strategic question through two workflows: a local filesystem agent reading files directly vs Vrin's graph-aware retrieval. Same AI, same documents, same question. Here's what we found.

Apr 910 min read
benchmarksmulti-hop-reasoning

Benchmark Results: 95.1% on MultiHop-RAG and 28% Better Than Academic SOTA on MuSiQue

We evaluated Vrin on two standard multi-hop reasoning benchmarks. The results: 95.1% accuracy on MultiHop-RAG (vs. 78.9% for GPT-5.2) and 28% improvement over HippoRAG 2 on MuSiQue. Here is exactly how we tested, what we found, and what it means.

Mar 2312 min read
ai-agentsintegration

One Integration, Hundreds of Deployments: Building AI Agents on Vrin

Vertical AI companies are embedding Vrin as the reasoning layer behind their agents. Here is how the architecture works, why data sovereignty scales per customer, and what the integration looks like in practice.

Mar 2310 min read
knowledge-infrastructureknowledge-reasoning

What Is Knowledge Reasoning Infrastructure?

RAG was built for retrieval, not reasoning. Knowledge Reasoning Infrastructure is the missing layer between your documents and your AI models, enabling multi-hop reasoning with traceable, auditable answers.

Mar 199 min read
vector-searchmulti-hop-reasoning

Why Vector Search Fails for Multi-Document Questions

Vector search finds similar text. But enterprise questions require traversing relationships across documents, timelines, and entities. Here's why similarity isn't reasoning, and what actually works.

Mar 198 min read
reasoningknowledge-graph

The Reasoning Gap: Why RAG Systems Fail and What Comes Next

Enterprise AI has a reasoning problem. RAG was built for retrieval, but enterprises need answers that require structured thinking across documents, timelines, and constraints. Here's how we're closing that gap.

Feb 1715 min read
brainstormingcreativity

Why Enterprise AI Plays It Safe (And How We Built Controlled Creativity)

Enterprise AI tools suppress creativity to avoid hallucinations. We took a different approach: controlled creativity validated against your knowledge graph. The result? 11-25% better strategic ideas than Gemini 3 Pro and ChatGPT 5.2.

Jan 510 min read
Topics

Technical Deep Dives

Architecture, implementation details, and engineering insights

Research & Benchmarks

Performance analysis, comparisons, and academic findings

Product Updates

New features, improvements, and roadmap

Company News

Team updates, partnerships, and announcements