Rethinking Legacy Data Infrastructure with Eon Co-Founders Ofir Ehrlich and Gonen Stein
In a Nutshell
Eon built a cloud data foundation that maps, classifies, ingests, and exposes enterprise data for AI use while preserving security, compliance, and cost efficiency. The biggest shift is that AI agents—non-human actors with legitimate access—now pose the same threats as ransomware but at far higher velocity, forcing companies to assume breach and rebuild data infrastructure for dynamic, multi-agent workflows. Real-world enterprise data has become a strategic asset and acquisition target, turning historical “backup” data into high-value training fuel that differentiates companies in an otherwise level AI playing field.
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Up until now, the concerns came from human threats. What we're seeing now on steroids is that the same type of threat is coming from non-human actors, agents that essentially have legitimate access to the environment with legitimate permissions. Fortunately for us, it's a very similar methodology in terms of detecting that and protecting against that. But the velocity of that happening is extreme.
Think of the non-technical people. They're not even aware for things like security or compliance or who is going to use this data. Maybe their agent that they are building are using other agents and they're not technical to even understand what it means. It creates complete set of actors inside the organization not bound by the rules of the organization and not necessarily running within the premises of the organization but handling sensitive data. It's a good thing and bad thing that everyone inside organization can become builders. We live in very interesting times.
Today on no prior we're joined by Ofir Ehrlich and Gonen Stein the co-founders of Eon. Eon is a cloud backup disaster recovery centric services designed for the AI era. In this discussion we talk about data AI why Google bought out the data of Spirit Airlines out of bankruptcy and what it means to really manage and use data infrastructure in the AI era.
What we do at a high level is we've created a new data foundation that runs in the cloud and we provide multiple capabilities that allow customers to first map and classify their data across their environment across multiple hyperscalers and identify what they have where they have it what's sensitive not sensitive and so on and so forth. Then we provide an ability to easily ingest that data from all these different sources structured unstructured data into this data foundation. And the data foundation then provides a very cost effective way of both maintaining the data for protection and recovery but also makes sense of the data. So it allows customers to very easily access it, query it, search through it and apply their AI models and LLMs on top of that data that's ingested from a variety of sources.
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