Kate Sai kishore

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Tastemaker
Tastemaker
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Maker History

  • qbrin
    qbrin Enterprise AI trust layer with citations & 20x fewer tokens
    Jul 2026
  • 🎉
    Joined Product HuntJuly 4th, 2026

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Token efficiency is part of Qbrin’s moat

Most RAG systems solve reliability by throwing more context into the model.

More chunks.
More tokens.
Bigger context windows.
More cost.

Its no more about connectors. It is trust.

Most enterprise AI products are racing to connect more tools: Slack, Gmail, Drive, Notion, Jira, Confluence, databases, and CRMs.

But connectors are becoming commoditized.

Why Qbrin is not another “company brain”

Most company brain products focus on giving AI access to more company data: docs, Slack, Gmail, tickets, wikis, and databases.

But access is not the same as trust.

Qbrin is built for AI agents that need to work in real enterprise environments, where a wrong answer can create serious risk. Instead of just retrieving the nearest document and generating a confident response, Qbrin organizes company knowledge with permissions, provenance, citations, freshness, entity relationships, evidence paths, contradiction handling, and abstention.

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