Tensor9 Deploys Software Anywhere with Digital Twins
▼ Summary
– Enterprises seek AI tools but avoid third-party SaaS due to data security concerns, prompting Tensor9 to help deploy software directly into customers’ tech stacks.
– Tensor9 converts vendor code for deployment in any customer environment (cloud to bare metal) and uses digital twin technology for remote monitoring and debugging.
– Tensor9 differentiates itself from competitors by enabling software deployment across diverse premises and offering real-time monitoring via digital twins.
– The company recently raised $4M in seed funding to expand hiring and develop next-gen tech for broader industry applications beyond its initial focus on voice AI.
– Tensor9’s founders, including ex-AWS engineers, identified the need for on-premise software solutions after recognizing enterprises’ reluctance to share sensitive data externally.\
Businesses increasingly demand cutting-edge AI and software solutions but face security risks when sharing sensitive data with external SaaS providers. Tensor9 addresses this challenge by enabling software vendors to deploy their products directly into a client’s existing infrastructure. The platform converts vendor code into compatible formats while creating digital twins—virtual replicas of the deployed environment—allowing real-time monitoring across cloud, on-premise, or bare-metal systems.
Michael Ten-Pow, Tensor9’s CEO and former AWS engineer, explains their differentiation: competitors like Octopus Deploy or Nuon facilitate deployments, but Tensor9’s digital twin technology provides unmatched visibility. “Enterprises need more than just deployed software—they require operational insights, debugging capabilities, and issue resolution without compromising data security,” he emphasizes.
The surge in AI adoption has accelerated demand for Tensor9’s solution. Financial institutions and corporations hesitate to expose proprietary data to third-party AI tools. Ten-Pow illustrates: “Imagine an enterprise search vendor asking J.P. Morgan for access to petabytes of internal data—it’s a non-starter. Our approach lets AI run securely within the client’s ecosystem.”
Tensor9 emerged from Ten-Pow’s earlier attempt to streamline SOC 2 compliance for vendors. Customer feedback revealed a broader pain point: enterprises wanted software running natively in their environments, but most startups lacked resources for custom on-premise deployments. This insight led to Tensor9’s 2024 launch, with ex-AWS colleagues Matthew Michie and Matthew Shanker joining as co-founders.
Initially adopted by voice AI firms like 11x and Retell AI, Tensor9 now serves enterprise search, database management, and data analytics sectors. After bootstrapping for a year, the company secured $4 million in seed funding led by Wing VC, with participation from Level Up Ventures and NVAngels. Investors recognized the problem firsthand—many portfolio companies struggled with secure software deployment.
Ten-Pow notes the technical complexity behind their seemingly simple model: “Solving hard infrastructure challenges convinced investors we’re the right team.” The funding will expand engineering talent and extend platform capabilities to new industries.
Looking ahead, Ten-Pow envisions a hybrid future: “The shift from on-premise to cloud was just phase one. The next evolution is software operating precisely where it’s needed, blending the best of both worlds.” Tensor9’s technology aims to make this vision a reality for security-conscious enterprises.
(Source: TechCrunch)
