The podcast discusses how AI and agentic workflows are transforming enterprise data infrastructure, making legacy data a critical asset for training models. Eon's co-founders explain their platform's role in mapping, classifying, and activating dormant data for AI applications, while highlighting new security challenges from non-human agents. They compare the current AI-driven shift to the earlier cloud migration, noting it's happening faster and creating urgent demand for tools that balance innovation with control.
Summarized by Podsumo
Eon provides a data foundation that maps, classifies, and ingests structured and unstructured data across hyperscalers, enabling cost-effective storage, querying, and AI model application.
Google's purchase of Spirit Airlines' data for $10 million illustrates the growing value of enterprise data sets for AI training, with competitors like Mercore also bidding.
The rise of AI agents creates a 'non-human threat' that mirrors ransomware but acts at extreme velocity, requiring new detection and recovery methods.
Eon addresses the challenge of multiple business unit owners locking data, offering continuous ingestion without compromising production or compliance.
The current AI transformation is happening faster than cloud adoption, driven by board-level pressure and new consumption models like product-led growth and forward-deployed engineers.
"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."
"It creates a 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."
"Today you understand that you can collect if you're able to smartly collect and clean all your data⦠and if you can activate it efficiently, you can let that team go wild with all the data that they have."