Most enterprise AI initiatives don't fail because the model isn't good enough. They fail because nobody organized the data underneath it.
Most enterprise AI initiatives don't fail because the model isn't good enough. They fail because nobody organized the data underneath it — so every new agent has to re-solve the same problem from scratch.
Matriq exists to fix that: one governed context layer that every agent, tool, or dashboard you build can rely on.
The hard part was never picking a model. It's knowing what "active customer" means at your company — and making sure every agent knows it too.
You can't reliably build agents on ungoverned data. The foundation has to come first.
Every early partner gets direct access to the team building this. Your workflows shape the roadmap.
Read-only by default, governed by your existing permissions, deployable inside your own environment.
Mohit Telang
Founder
I've spent the last decade leading data teams, and watched the same story play out at every company: brilliant operators stuck waiting on reports, good analysts burning most of their week firefighting broken dashboards, and institutional knowledge trapped in people's heads. The shape of the problem is the same everywhere — and the fix doesn't need another BI tool. It needs a foundation that actually understands your business, and agents that can build on it. That's what I'm building with Matriq. If that resonates, I'd love to talk.
Every early customer gets direct founder access. Your feedback shapes what we build next — and what we drop.
Your data stays in your environment. Read-only access. User-level permissions carry over from every connected source.
No per-seat games. No "contact us" maze for small teams. Pricing scales with value, not headcount.
A live walkthrough on your kind of data. Real questions, real answers.
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