In this Mixture of Experts segment, Saket Saurabh, co-founder and chief executive officer of Nexla, joins theCUBE’s John Furrier to discuss the critical shift from traditional data engineering to "context engineering" in the era of generative AI. Saurabh explains that while AI models are powerful, their true value in the enterprise is unlocked only when fed the right context – a complex mix of raw data, semantic meaning and knowledge buried in documents. He outlines how the role of data is flipping from curating specific datasets for analytics dashboards to connecting virtually every system to allow AI to make informed decisions and execute actions.
The conversation delves into the architectural changes required to support "AI factories," moving beyond static IT stacks to dynamic, low-latency data products. Saurabh details the necessity of a robust abstraction layer that handles connectivity, semantics and delivery, likening it to a TCP/IP stack for enterprise intelligence. He also highlights how Nexla is utilizing AI to automate the creation of connectors for brittle legacy systems, ensuring that agentic flows and large language models can reliably access and act upon data across the organization. The discussion concludes with insights on the evolution of ecosystem protocols like MCP and the need for rigorous testing to ensure AI reliability in chaotic enterprise environments.
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Saket Saurabh, Nexla
In this Mixture of Experts segment, Saket Saurabh, co-founder and chief executive officer of Nexla, joins theCUBE’s John Furrier to discuss the critical shift from traditional data engineering to "context engineering" in the era of generative AI. Saurabh explains that while AI models are powerful, their true value in the enterprise is unlocked only when fed the right context – a complex mix of raw data, semantic meaning and knowledge buried in documents. He outlines how the role of data is flipping from curating specific datasets for analytics dashboards to connecting virtually every system to allow AI to make informed decisions and execute actions.
The conversation delves into the architectural changes required to support "AI factories," moving beyond static IT stacks to dynamic, low-latency data products. Saurabh details the necessity of a robust abstraction layer that handles connectivity, semantics and delivery, likening it to a TCP/IP stack for enterprise intelligence. He also highlights how Nexla is utilizing AI to automate the creation of connectors for brittle legacy systems, ensuring that agentic flows and large language models can reliably access and act upon data across the organization. The discussion concludes with insights on the evolution of ecosystem protocols like MCP and the need for rigorous testing to ensure AI reliability in chaotic enterprise environments.
In this Mixture of Experts segment, Saket Saurabh, co-founder and chief executive officer of Nexla, joins theCUBE’s John Furrier to discuss the critical shift from traditional data engineering to "context engineering" in the era of generative AI. Saurabh explains that while AI models are powerful, their true value in the enterprise is unlocked only when fed the right context – a complex mix of raw data, semantic meaning and knowledge buried in documents. He outlines how the role of data is flipping from curating specific datasets for analytics dashboards to c...Read more
