For decades, cybersecurity has relied on reactive methods — detecting, analyzing and responding to threats after they infiltrate systems. The digital landscape is shifting toward proactive cybersecurity, and Deep Instinct Inc. is a leader in that shift.

“The challenge I always faced with even my last few companies was the ability to prevent threats before they happen,” said Lane Bess (pictured, right), chief executive officer of Deep Instinct. “A lot of technology layers of defense and great technology, but the real challenge that we had to face was how do we get the [artificial intelligence] science — in particular, the tech is called Deep Learning Science and Neural Network Science — to put ourselves in a position of prevention first?”

Bess and Carl Froggett (left), chief information officer of Deep Instinct, spoke with theCUBE’s Rebecca Knight for the Tech Innovation CUBEd Awards 2025 interview series, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how Deep Instinct is paving the way for a more resilient digital future by prioritizing prevention over detection and response.

DXS brings proactive cybersecurity to the forefront

Unlike traditional systems that rely on signatures and machine learning, Deep Instinct’s DSX platform harnesses deep neural networks to detect and block threats preemptively. It applies deep learning across various security domains, including cloud storage, applications and endpoints, strengthening an organization’s security posture and streamlining operations by reducing security operations center fatigue, according to Froggett. In recognition of these advancements, the company received a CUBEd “Top AI Innovation for Security” award.

“With DSX, we’re able to take that core differentiator, that unique value we have, and apply it into different areas of an enterprise’s security stack,” Froggett said. “That flexibility of being able to bring that deep learning core and that prevention-first approach makes it very unique in the market.”

Malicious actors are now using AI, including large language models, to generate sophisticated malware on demand. This shift in attack methodology demands an equally sophisticated defense mechanism. Deep Instinct’s AI-driven prevention model effectively neutralizes these threats in real-time, bridging the latency between threat and defense proliferation, according to Froggett.

“We have a very flexible deployment model that plays well, especially into some of the more modern shift-left agile development as we move to cloud and software stacks,” he said. “You can take the same fundamental deep learning core that we have and apply it in many different use cases.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage for the Tech Innovation CUBEd Awards 2025 interview series: 

Photo: SiliconANGLE