Enterprises want cutting-edge AI software but they don’t want their sensitive data leaving the building. That’s where Tensor9 steps in. The startup is helping software vendors land major enterprise deals by making it simple to deploy directly into a customer’s own tech environment—no cloud handoff required.
With a fresh $4 million seed round led by Wing VC, Tensor9 is building the tools that allow software vendors to operate inside enterprise infrastructure without needing to custom-build on-premise versions for every deal. The secret weapon? Digital twins that mirror live deployments and make remote monitoring seamless.
Deploy Anywhere, Monitor Everything
Founded in 2024 by former AWS engineer Michael Ten-Pow, Tensor9 converts a software vendor’s code into a format that’s ready for any customer environment—from public cloud to private data centers to bare metal. Then, it creates a “digital twin” of that deployment so vendors can still monitor, debug, and maintain their product—even if it never leaves the customer’s secure perimeter.
“You can’t just throw a piece of software over the wall and expect it to work,” Ten-Pow said. “Our platform makes sure vendors can see what’s running, understand what’s going wrong, and fix it—without ever touching the customer’s data.”
Tensor9 stands out in a crowded deployment space by making fully private, compliant installations easy to monitor and support. That’s a major upgrade over legacy platforms like Octopus Deploy or Nuon, which often fall short when it comes to visibility and observability inside enterprise networks.
Solving a Growing AI Deployment Dilemma
The rise of AI tools is creating a new kind of friction between software vendors and data-sensitive industries. Ten-Pow shared a telling example: an enterprise search company approaching J.P. Morgan for a proof of concept. Asking for access to six petabytes of internal data? Not going to happen. That’s where Tensor9 comes in—letting the software live where the data already resides.
The company first gained traction with voice AI startups needing secure deployments. Since then, it’s expanded into enterprise search, data management, and databases, supporting teams like 11x, Retell AI, and Dyna AI.
Ten-Pow originally set out to solve a different problem—streamlining SOC 2 certification. But during customer discovery, he found that what enterprise buyers really wanted wasn’t compliance paperwork. They wanted vendors to just run the software inside their stack. That insight became the foundation of Tensor9.
Ten-Pow later recruited two former AWS colleagues, Matthew Michie and Matthew Shanker, to join as co-founders. Together, they bootstrapped the company through its first year.
Backed by Investors Who’ve Seen the Problem Firsthand
The $4 million seed round came together quickly. Alongside Wing VC, the round included Level Up Ventures, Devang Sachdev of Model Ventures, and NVAngels, a group of ex-Nvidia engineers, plus other individual angels. According to Ten-Pow, it wasn’t hard to find believers—the VCs had seen their portfolio companies struggle with the exact deployment roadblocks Tensor9 is solving.
Now, the startup is hiring and building out the next generation of its platform to support more industries and more complex deployments.
“There’s been a shift from on-prem to the cloud, and now we’re seeing the next evolution: software that operates wherever it needs to, without sacrificing control or compliance,” Ten-Pow said. “That’s the synthesis Tensor9 is betting on.”
