Enterprise storage enhanced with AI and ML in Infinidat

Is there a place for artificial intelligence and machine learning in today's enterprise storage technology? Infinidat Ltd.'s data storage system offering demonstrates how to leverage AI/ML for large-scale primary storage.

Eric Herzog, CMO at Infinidat, talks about TheCube and Enterprise Storage.

Infinidat employs neural cache, a patented technology driven by AI and machine learning technology, intelligently positions data in layered storage designs. According to Eric Herzog, Chief Marketing Officer at Infinidat (pictured), this is a process that will be enhanced immediately.

“If you use a flash array, filling it up makes it slower,” Herzog explained. “What do you do? You need to buy another flash array to run more workloads. With us, that won't happen. It's all done with the ability to use AI and ML to manage the placement of your data. There are other technologies to show you.

Herzog spoke with TheCube's Christophe Bertrand at the Data Protection & AI Summit during an exclusive broadcast on TheCube, Siliconangle Media's LiveStreaming Studio. They discussed the evolving role of AI and ML on storage performance and protection. (*Disclosure below.)

Reduce the threat window for enterprise storage

In addition to data placement, Infinidat also focuses on AI and ML leverage for a product called Infinisafe Cyber ​​Detection. According to Herzog, the company is partnering with Index Engines Inc. to reduce threat windows and provide reliable storage recovery services.

“No matter how big it is, you can recover your primary storage within a minute,” Herzog said. “But you still need to make sure it's a known good copy. Infinizafe's Cyber ​​Detection uses the partner's index engine to obtain candidates, place them in a fenced forensic environment, and scan them. AI is used as an early warning system.”

Infinidat has also become an enabler of searched generation inference as customers became increasingly transformed into larger language models for workload delivery. The company's RAG workflow deployment architecture allows customers to use Infinibox and Infinibox SSA primary storage to optimize AI model output without the need for special equipment. According to Herzog, this ability has become more important as businesses try to leverage their own data.

“I want to use my own data for my AI workloads,” he said. “We have our own AI RAG technology, Search Extension Generation. This works with our competitors as long as we expose the NFS protocols that all our databases do, not just our own storage.”

Infinidat's approach is based on the reality that AI is driven by data and cannot function properly when storage is corrupted. According to HERZOG, using AI and ML to deliver resilience and performance makes sense as the role of storage becomes more important in driving enterprise workloads.

“It's all data,” Herzog said. “The core is data. So, primary storage requires next-generation data protection. This is what AI uses. Backups also require next-generation data protection. You need to make sure it's clean using AI and ML technology with cyber protection.”

This is a complete video interview that is part of Siliconangle and part of TheCube's reporting on Data Protection & AI Summit.

https://www.youtube.com/watch?v=v4tqx9-jnpm

(*Disclosure: Infinidat Ltd. sponsored the TheCube segment of this segment. Neither Infinidat nor any other sponsors edit the content of TheCube or siliconangle.)

Photo: Silicon Angle