Deploy Software Anywhere with Digital Twins | tensor9

Addressing Enterprise Concerns with Secure Software Deployment

Many enterprises are eager to integrate new software and AI tools into their operations. However, a significant obstacle exists: the risk associated with transmitting sensitive data to third-party Software-as-a-Service (SaaS) providers.

Introducing Tensor9: Bridging the Deployment Gap

Tensor9 aims to resolve this challenge by enabling software companies to deploy their applications directly within a customer’s existing technological infrastructure. This approach allows enterprises to maintain complete control over their data.

How Tensor9 Facilitates Secure Deployment

The core function of Tensor9 involves converting a software vendor’s code into a format compatible with the client’s specific tech environment. Subsequently, a digital twin is created.

This digital twin, essentially a scaled-down model of the deployed software’s infrastructure, allows customers to remotely monitor performance and identify potential issues.

Versatile Deployment Options

Tensor9 supports deployment across a wide range of environments, encompassing cloud platforms, as well as traditional bare metal servers. This flexibility caters to diverse enterprise needs.

Differentiating Factors in a Competitive Landscape

According to Michael Ten-Pow, co-founder and CEO of Tensor9, the company’s ability to deploy software to any location, coupled with its digital twin technology for remote monitoring, sets it apart from competitors like Octopus Deploy and Nuon.

The Importance of Visibility and Control

“Successfully integrating software requires more than simply transferring it; it demands ongoing visibility and the ability to diagnose and resolve problems effectively,” Ten-Pow explained. “Our platform provides the tools for this crucial oversight.”

The Rising Demand Driven by AI

The timing for Tensor9’s technology is particularly opportune, coinciding with the rapid growth of AI. Enterprises, especially those in the financial sector, are keen to leverage AI but are understandably hesitant to share their data externally.

Data Security in AI Adoption

Ten-Pow illustrated this point with an example: “A search vendor proposing to J.P. Morgan that they require access to six petabytes of data to build an intelligent search layer would likely face insurmountable resistance.”

From AWS Engineer to Founder

Ten-Pow, formerly an engineer at AWS, described his journey to founding Tensor9 as “long and winding.” The initial concept evolved after recognizing a critical need within the market.

Identifying the Core Enterprise Need

Early explorations focused on simplifying SOC 2 certification for software vendors. However, customer feedback revealed a more fundamental desire: the ability to run software directly within their own secure environments.

The Genesis of Tensor9

This insight led to the launch of Tensor9 in 2024. Later that year, Matthew Michie and Matthew Shanker, both former AWS colleagues, joined as co-founders.

Early Traction and Expanding Verticals

The company initially gained traction with voice AI companies. They have since broadened their focus to include enterprise search, databases, and data management solutions.

Current clients include 11x, Retell AI, and Dyna AI, among others.

Securing Seed Funding

Tensor9 operated on a bootstrapped basis for its first year before securing a $4 million seed round. The round was led by Wing VC, with participation from Level Up Ventures, Model Ventures, NVAngels, and other angel investors.

Investor Confidence and Technical Expertise

Ten-Pow noted that attracting investors was relatively straightforward, as many VCs had observed their portfolio companies grappling with similar deployment challenges. The key was demonstrating Tensor9’s technical capabilities and the strength of its team.

A Complex Solution with a Simple Model

“While our model appears straightforward, it’s underpinned by significant technical complexity. We’ve overcome substantial hurdles to deliver this functionality,” Ten-Pow stated.

Future Plans: Growth and Technological Advancement

The newly acquired funding will be allocated to expanding the team and developing the next iteration of Tensor9’s technology. This will enable the company to serve a wider range of industries.

The Evolution of Software Deployment

“We’re witnessing a shift from traditional on-premise solutions to the cloud, and now towards a model where software resides and operates where it’s most effective – a synthesis of both approaches,” Ten-Pow concluded.