Companies in today's world are eager to utilize cutting-edge software and AI tools, but handing over their crucial data to third-party Software-as-a-Service (SaaS) providers often comes with its risk. That's where Tensor9 steps in. Their goal is simple: assist software companies in gaining a larger enterprise client base by enabling them to install their software directly into the client’s technical infrastructure.

To make this possible, Tensor9 translates the code from the software vendors into a format that can easily be integrated into the clients' technology. For better understanding and monitoring, Tensor9 creates a digital twin of the deployed software, which is essentially a scaled-down model of its infrastructure. What's great about Tensor9 is its versatility – it can support deployments in any setting, be it cloud or bare metal servers.

In a conversation with TechCrunch, Michael Ten-Pow, the co-founder and CEO of Tensor9, gave insights into what makes Tensor9 stand out from competitors like Octopus Deploy and Nuon. He stressed the advantages of their digital twin technology and their ability to extend software to any premises seamlessly.

In Michael's own words, launching a software is not a mere act of "throwing it over the wall". It requires understanding, debugging, and troubleshooting to ensure it runs well. This is exactly what Tensor9 facilitates. As businesses increasingly aim to adopt AI technology, ten-Pow's efforts arrive just in time. Their services ensure corporate entities can use AI without risking their sensitive data by outsourcing to a third party.

Interestingly, the conception of Tensor9 stemmed from Ten-Pow's shortcoming with another venture. However, during this process, he realized that many businesses yearned for software tooperate within their own technology environment. Based on this realization, Ten-Pow began the Tensor9 adventure in 2024. Later in the year, he was joined by Matthew Shanker and Matthew Michie, two of his former AWS colleagues.

Initially, Tensor9 found acceptance among voice AI companies. Recently, it has begun to branch out into various other sectors, including enterprise search, databases, and data management, while collaborating with top AI firms, such as 11x, Retell AI, and Dyna AI.

In its initial stage, Tensor9 was self-funded. Later, it raised $4 million in initial money, led by Wing VC and backed by NVAngels, Level Up Ventures, Devang Sachdev of Model Ventures, and other angel investors. Convincing investors didn't prove much of a challenge since they had already seen similar struggles within their portfolio companies. From here, Tensor9 intends to target more industry verticals, grow its workforce, and improve its technology.