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Articles tagged with #llm
Traditional data security controls what users can read. AI analytics also needs to consider what users can derive. Imagine a user who cannot access: employee.salary But the same user can access: depa
A database connection makes an AI agent data-aware. It does not make it business-aware. Connect a new data agent to an enterprise database and it can quickly discover: Tables Columns Data Types Primar
If your Text-to-SQL benchmark only tests clean questions against clean schemas, you are measuring the demo—not the production system. Text-to-SQL has improved quickly. Give a modern system a well-defi
A production Text-to-SQL agent should not generate SQL simply because it can interpret a question. It should first decide whether the business intent is clear enough to query safely. Consider: Show m
If enterprise AI knows what data means but not where that meaning stops being valid, it still does not understand the data well enough to use it reliably. When teams improve an AI data agent, the stra
A production AI data system should not only tell users what the answer is. It should preserve enough evidence to show why that answer is trustworthy. AI data agents have improved quickly. They can tra
