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Russian (RU) Paula Tudoran
Fri, May 23, 2025, 10:01 AM 4 min read
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Seattle-based startup Tensor9 has raised a $4 million seed round to reshape how enterprise software, especially AI tools, is deployed inside high-security environments. The company is led by Michael Ten-Pow, a former Amazon Web Services engineer with over a decade of cloud infrastructure experience at Amazon (NASDAQ:AMZN).
Founded in 2023, Tensor9 has already attracted the attention of heavy-hitting investors. Wing VC led the round, joined by Level Up Ventures, Model Ventures' Devang Sachdev, and NVAngels, a group of ex-Nvidia (NASDAQ:NVDA) professionals, according to GeekWire.
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According to TechCrunch, Tensor9 is focused on solving a growing problem: how to let vendors deliver advanced AI software to enterprise clients without forcing sensitive data out of its original environment.
TechCrunch says that the company enables vendors to install their software directly into a client's existing tech infrastructure, whether it lives in the cloud, on-premise, or on bare metal servers. Instead of shipping data to a software-as-a-service platform, vendors can now deploy code inside a customer's walls, which is crucial for industries like finance, healthcare, and government.
Tensor9 uses a digital twin architecture to make this possible. Each customer environment is mirrored through a virtual replica, which allows vendors to monitor, support, and update deployed software without breaching any privacy firewalls. Logs, metrics, and even hardware issues are fed back to this virtual twin in real time, GeekWire says.
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“You can't just throw a piece of software over the wall, or it's very difficult to throw a piece of software over the wall, and know what's going on, be able to find issues, debug them, fix them,” Tensor9 CEO Ten-Pow told TechCrunch. “They see it running, they can debug it, they can log in and understand what the issues are and fix them.”
Tensor9 began as a bootstrapped project after Ten-Pow realized that System and Organization Controls 2 compliance wasn't the real obstacle stopping startups from closing enterprise deals. Instead, companies wanted software that could run locally, under their own control, with no risk to data sovereignty, TechCrunch reports.
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