UPDATED 11:20 EDT / DECEMBER 05 2024

Nitish Shrivastava, senior vice president and head of products business at Persistent, and Pradeep Sharma, engineering lead at Persistent, talk about SASVA 2.0 at Cloud AWS re:Invent 2024. AI

Persistent Systems deepens focus on deterministic AI with SASVA 2.0

Persistent Systems Ltd. aims to create a timeless and relevant technology with SASVA 2.0, a platform that supports software development with deterministic and generative artificial intelligence.

The technology services company works with a variety of sectors, including financial services, airports and healthcare, all of which are feeling the impact of the gen AI wave. Persistent Systems’ platform enables users to build personalized AI solutions.

Nitish Shrivastava, senior vice president and head of products business at Persistent, and Pradeep Kumar, engineering lead at Persistent, discuss why deterministic AI is so important with SASVA in a conversation with theCUBE.

Persistent’s Nitish Shrivastava and Pradeep Sharma talk about deterministic AI.

“Software engineering is evolving from a traditional product engineering approach to something where the virtual agents are going to collaborate,” said Nitish Shrivastava (pictured, left), senior vice president and head of products business at Persistent. “That is where we spin this thing as a service-as-a-software enabled by virtual agents. This is a platform which is not only doing product engineering, but right from it is doing from a product requirement, gathering, grooming, creating user stories, assisting developers, assisting the quality initiative all the way to taking it down to a CI/CD pipeline.”

Shrivastava and Pradeep Sharma (pictured), chief architect at Persistent Systems, spoke with theCUBE Research’s John Furrier for theCUBE’s “Cloud AWS re:Invent Coverage,” during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how SASVA supports AI development

Reigning in the AI horse with SASVA 2.0

Persistent has been working with AI for a long time, with the goal of solving the issue of machine learning reliability, according to Shrivastava and Sharma. Gen AI models can be notoriously capricious and produce “hallucinations” that interfere with drawing accurate conclusions about data.

“In SASVA, basically we are trying to solve a complex business problem,” Sharma said. “If you look at generative AI, it’s like a horse which is just going openly very fast in any direction … but if you want to put it for actual use, you need to bring determinism into it, just like putting that blinkers on top of that horse so that you take it in the desired direction.”

SASVA takes a deterministic approach to AI and is built with four qualities in mind: affordability, security, personalization and responsible AI. Its virtual agents are designed to reliably and accurately enhance the developer’s experience.

“Products are not built in silos,” Sharma explained. “Whenever we are generating a new code, we need to make sure that we are not breaking this compatibility … we actually mine millions of repositories that [are] available publicly as well as privately. We come up with our own data set so that we know that what are the things that are compatible with each other across the stack from operating system.”

Persistent has already seen great success with SASVA in its network of partnerships. For example, the company worked with a software company in Europe — a region highly sensitive to data use — to greatly improve employee productivity, according to Shrivastava.

“Productivity is not about doing the same work with 350 people,” he said. “It is about bringing technology and help[ing] these 550 to deliver maybe a thousand people worth of jobs. In that particular case, the idea was to infuse a model where … the new [employees] who come into their ecosystem can become productive on day one. They’re going to start making significant contributions.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s “Cloud AWS re:Invent Coverage”:

Photo: SiliconANGLE

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