Enterprises are keen to leverage advanced software and AI tools but remain hesitant to share sensitive data with third-party SaaS providers. Tensor9 aims to bridge this gap by enabling software vendors to integrate their applications directly within a customer’s existing technology ecosystem.
Tensor9 works by transforming a software vendor’s code into a deployable format tailored for the client’s unique infrastructure. Additionally, it creates a digital twin— a miniature model of the deployed software— allowing customers to effectively monitor its performance in their environment. This capability extends across diverse settings, including cloud and physical servers.
Co-founder and CEO Michael Ten-Pow highlighted Tensor9’s distinctive approach, specifically its ability to facilitate deployment across various environments and its innovative use of digital twin technology that enhances remote monitoring. This functionality stands out in contrast to other deployment solutions such as Octopus Deploy and Nuon, as it allows enterprises to observe and troubleshoot issues directly.
Ten-Pow acknowledged the pressing need for such technology, particularly as more enterprises, including financial institutions, seek to adopt AI innovations while safeguarding their data from third-party exposure. He illustrated this concern with the example of an enterprise search vendor needing access to vast amounts of sensitive data to create an intelligent search feature, which would be unacceptable for many organisations.
Having previously worked as an engineer at AWS, Ten-Pow’s journey to founding Tensor9 was marked by discovering the need for software to function seamlessly within an enterprise’s infrastructure. Traditional software companies, particularly startups, are often ill-equipped to provide customized, on-premises environments for each client.
Launched in 2024, Tensor9 gained immediate traction in the voice AI sector and is now expanding its services across other industries such as enterprise search and data management, collaborating with firms like 11x, Retell AI, and Dyna AI.
Initially self-funded, Tensor9 secured a $4 million seed funding round, led by Wing VC and supported by other investors, including Level Up Ventures and angel investors from the tech sector. Ten-Pow noted that interest from investors was relatively straightforward, as many had witnessed similar challenges faced by their portfolio companies, making the case for Tensor9’s solution compelling.
The funding will primarily support hiring efforts and technology development, allowing the company to broaden its reach into new sectors. Ten-Pow concluded by reflecting on the software industry’s evolution, emphasizing the need for applications to operate where they are most effective— blending the principles of on-premise and cloud solutions into a coherent model that addresses contemporary enterprise needs.
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