10+ hours of podcasts, in 5 minutes.
3 quotes from 1 episode on No Priors, each with a timestamped link to the source.
Gonen Stein stated that enterprise AI stalls when historical records remain locked in expensive databases and rapid agent deployments cause operational chaos. Converting passive data into an efficient foundation creates a safe training pipeline for new models.
Converting existing customer data into a new foundation format enables automated mapping, classification, and access control for AI workflows.
“We're able to take what customers already have, convert it into this new data foundation format that's much more stored much more efficiently and provide the mapping, classification, access control, and connect it into the AI workflows.”
Historical training data sits in disconnected systems across the organization. These records remain locked within customer environments, creating access barriers and high expenses for data pipelines.
“…it's kept in their environment in different forms but it's locked. It's not accessible and usually it's very very expensive.”
Generative systems spread quickly across organizations without operational guardrails. Customers lose control over these rapid transformations, turning the technology into a business inhibitor.
“What we're seeing now in the this crazy world of of AI and agents is that those transformations are happening way faster and customers are losing control to a point where that's becoming an inhibitor, right? Not an enabler.”
From Why Enterprise AI Deployments Demand Forward Deployed Engineers
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