TECHNOLOGY

Software's New Home: How Digital Twins Are Changing the Game

Berkeley, CA, USAWed May 14 2025
A new player has entered the tech scene, aiming to make software deployment easier and more secure. Tensor9 is tackling a big problem in the tech world. Companies want to use new software and AI tools, but they don't want to risk sending their sensitive data to third-party services. Tensor9 helps software companies deploy their products directly into a customer's tech setup. This isn't just about putting software somewhere new. Tensor9 creates a digital twin, or a small model of the software's infrastructure. This model lets the software company monitor how their product is working in the customer's environment. Customers can see the software in action, spot issues, and fix them without any hassle. This approach is gaining traction, especially with the rise of AI. Enterprises and financial institutions want AI tech, but they can't risk sending their data to third-party services. Tensor9's tech is timely. It helps software companies, especially startups, offer on-premise options without needing a lot of resources. This is a big deal because many software companies struggle with this exact problem. Tensor9 isn't alone in this space, but its use of digital twin technology sets it apart. The company has already found early success with voice AI companies and is expanding to other areas like enterprise search and data management. Tensor9 has also secured funding to hire more people and develop its technology further. The future of software deployment might be about software living and operating where it needs to, blending old and new ideas. This could be the next big step in how software is used and managed. The idea of software living where it needs to, and operating where it needs to, is a synthesis of the previous on-premise and cloud ideas. This is a big deal because it could change how software is used and managed in the future.

questions

    How does Tensor9 ensure the security and integrity of the software during the deployment process?
    What are the potential challenges in creating digital twins for complex software infrastructures?
    How does Tensor9 verify that the digital twin accurately represents the deployed software?

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