Enterprises continually seek cutting-edge software and AI tools yet grapple with protecting their sensitive data, making traditional third-party software-as-a-service (SaaS) models potentially risky. Recognizing this gap, Tensor9, a startup founded in 2024, enables software vendors to securely deploy their products directly into an enterprise customer’s existing technology environment.
Leveraging deep technical expertise, Tensor9 transforms a software provider’s code into a compatible format for any deployment scenario—whether to cloud services or bare-metal servers. Crucially, it deploys digital twin technology to maintain a virtual replica of the vendor’s software in the customer’s infrastructure. This allows vendors real-time visibility, remote debugging capabilities, and the ability to swiftly identify and resolve problems as they occur in the customer’s environment.
Michael Ten-Pow, Tensor9’s CEO and co-founder, describes this approach as pivotal, particularly in today’s increasingly AI-driven business landscape. Enterprises, he notes, want AI-powered technology to derive insights from extensive internal datasets, but they hesitate to transfer such sensitive data externally. Consequently, the demand for Tensor9’s solution is rapidly growing.
Ten-Pow, who previously worked as an engineer at AWS, initially explored other startup ideas—such as simplifying cybersecurity compliance, including data security certifications like SOC 2—for vendors seeking enterprise customers. Yet conversations with potential clients revealed a more prevalent need: enterprises wanted software deployed within their own security perimeters. But while this demand was clear, small and midsize software providers typically lack resources for tailored, enterprise-specific installations.
From this insight, Tensor9 was born, with Ten-Pow quickly joined by fellow ex-AWS colleagues Matthew Michie and Matthew Shanker as co-founders. In their initial year, Tensor9 found significant traction within voice AI companies, notably serving firms like 11x, Retell AI, and Dyna AI. Since these early successes, Tensor9 has expanded its market reach into related software niches such as enterprise search, database management, and general data infrastructure solutions.
The venture spent its first year bootstrapping but recently secured a $4 million seed funding round. The financing round was led by Wing VC, with additional participation from Level Up Ventures, Devang Sachdev of Model Ventures, NVAngels (an investment group staffed by former Nvidia employees), and several other private angel investors. Investor interest proved robust, according to Ten-Pow, driven by the recognition that widespread difficulties in software deployment provided strong validation of Tensor9’s offerings. Proving the company’s capability to effectively tackle this complex challenge convinced backers of the team’s authenticity and technical leadership.
Ten-Pow noted that while the solution may appear straightforward externally, significant underlying complexity required deep, innovative engineering to ensure viability and seamless end-user experiences. Funds from the recent raise will primarily support hiring in key technical roles and further extending the company’s technology to new enterprise verticals.
Ultimately, Ten-Pow believes Tensor9 is ideally positioned at the interface between on-premises deployments and cloud environments, reflecting the industry’s growing preference for software that seamlessly operates wherever enterprises require it. This model, he argues, represents not only the future of software deployment but a natural progression from traditional data center-centric setups toward adaptive, hybrid computing models that fully respect and preserve customer data security.
