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  4. SE Radio 734: Sathiesh Veera on Engineering Data-Protection Guardrails with LLMs
SE Radio 734: Sathiesh Veera on Engineering Data-Protection Guardrails with LLMs

SE Radio 734: Sathiesh Veera on Engineering Data-Protection Guardrails with LLMs

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42:32

Sathiesh Veera, a GenAI Solutions Architect at
At&T, speaks with host Brijesh Ammanath about the
data-protection guardrails required when using LLMs. The core
issue is that LLMs sit outside the cloud tenant in most
enterprise AI deployments, which means that data leaves the
company's perimeter with every prompt, RAG retrieval, and tool
call. Contractual agreements can restrict the data that LLM
vendors are allowed to use for training and audits, but they
don't stop prompt injection or unintended exposure as company
data is often shared to LLMs via natural language queries, APIs,
tool and function calls, and MCPs. Sathiesh discusses ways to
employ security measures and data filtering at each layer to
conform to data security policies and protect the data. 

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