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Nand AI builds accurate enterprise AI systems that actually work in production. Nine out of ten enterprise GenAI pilots fail because of one problem: inaccuracy. Incomplete answers, outdated information, and confidently wrong responses erode trust and stall adoption. We solved this problem by building accuracy into the architecture from day one. Our platform achieves 90% recall and 95% accuracy - more than 5x better than standard RAG systems - across two products: Magus transforms RFP responses, security questionnaires, and CPQ generation from weeks of work into minutes of review. Sales teams using Magus close deals 30+ days faster. OneSearch fixes enterprise search by understanding context, not just similarity. When knowledge workers ask a question, they get the right answer with verifiable citations - not 400 irrelevant results to sift through. Both products are built on the same foundation: evaluation-oriented retrieval that validates every answer before it reaches your team. No hallucinations. No outdated information. No guessing which result is actually relevant. Founded by AI leaders from Microsoft Bing and Lyft, we're bringing production-grade accuracy to enterprise AI. Now available with self-serve access. The age of "pretty good" AI is over. Welcome to the age of accurate AI.

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Shiraz Zaman is the Founder and CEO of Nand AI.

6 people are employed at Nand AI.

Nand AI is based in San Francisco, California.

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