We don't build chatbots.
We build enterprise memory.
NoteHook Labs was founded to bridge the gap between AI potential and engineering reality.
The Origin Story
In 2024, the world fell in love with AI. Large Language Models became a household name. Every enterprise rushed to deploy their own "AI assistant."
By 2026, the hangover set in.
Companies realized that public LLMs were leaking sensitive data, hallucinating critical facts, and failing spectacularly on domain-specific questions.
The problem wasn't the models. The problem was the data pipeline.
NoteHook Labs was built to solve this "last mile" problem. We don't slap a chatbot onto your data. We engineer the entire context-retrieval system—from messy legacy files to precise, cited AI responses.
Our Manifesto
Three principles that guide every deployment.
Code is cheap; Context is expensive.
Anyone can spin up an LLM. The hard part is making it actually understand your domain. We obsess over the data pipeline—chunking strategies, re-ranking logic, embedding quality—because that's where precision lives.
Privacy is Binary.
You either own your data, or you don't. There's no "mostly private." We deploy exclusively in your infrastructure. Your documents never touch our servers. Your models never train public systems.
Invisible Infrastructure.
Our success is measured by how little you think about the backend. When the system "just works"—queries answered in seconds, sources cited perfectly, zero hallucinations—that's when we've done our job.
The Backstage Ninja Philosophy
We're not here to be in the spotlight. We're here to make you look brilliant.
Unlike "Big Tech" consultancies...
Accenture will spend 3 months on "discovery." McKinsey will give you a 200-slide deck about "AI strategy." We'll give you a working prototype in two weeks.
We're boutique by design. No layers of project managers between you and the engineer actually building the system. When you email us, you get an answer from someone who writes the code.
Unlike "GitHub darlings"...
Commodity open-source projects are great learning tools. But they lack governance, enterprise support, and the integration work that makes them actually useful in a corporate environment.
We take the best of open-source tooling and wrap it in proper infrastructure: Automated deployments, security hardening, monitoring, and ongoing maintenance.
Why "NoteHook"?
A hook is how you retrieve what you need. In fishing, you can't just throw a net and hope for the best—you need precision, patience, and the right bait.
Same with enterprise AI. Generic "search everything" approaches fail. NoteHook is about precision retrieval— hooking exactly the right context from your notes, documents, and databases to generate accurate, cited responses.
Plus, we're in a lab. Experimenting. Iterating. Always improving the hook.