As demand for generative AI accelerates across industries, enterprises are racing to adopt new software tools — without compromising data security. For most large organizations, handing sensitive internal data to SaaS providers isn’t an option. That’s where Tensor9 comes in.
Founded in 2024 by former AWS engineer Michael Ten-Pow, Tensor9 enables software vendors to deploy their AI tools directly inside a customer’s tech stack — whether in the cloud, on-premise, or on bare-metal servers. The startup doesn’t just handle the deployment. It also creates a digital twin of the deployed system, allowing vendors to remotely monitor performance, debug issues, and ensure reliability without ever accessing a customer’s data.
Ten-Pow said the idea emerged while exploring how to help startups meet cybersecurity certifications like SOC 2. But customer conversations revealed a deeper need: on-premise deployments that didn’t compromise on visibility. He believes you can’t just throw software over the wall. They want to run it in their environment — but you still need to support it.
Tensor9 has since found traction with AI vendors in voice and enterprise search, counting customers like 11x, Retell AI, and Dyna AI. The company recently raised a $4 million seed round led by Wing VC, bringing on former AWS colleagues Matthew Michie and Matthew Shanker as co-founders.
Ten-Pow believes Tensor9 represents a new phase in software infrastructure — one that bridges the cloud and on-premise divide.
Featured image: Credit: Tensor9
