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Building Enterprise AI Agents: Text-to-SQL and Structured Data for Answers Your Business Can Trust
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Publisher: Independently Published
Pages: 294
Weight: 0.87
Height: 0.62 Width: 6.00 Depth: 9.00
Language: English
You have the data. This book shows how to connect it with AI so your team can reach it more easily, turn it into information, and analyze it through natural language.
Every organization holds valuable structured data across databases, business applications, warehouses, lakes, spreadsheets, dashboards, and reports. These resources capture the activity, knowledge, and history of the business. Building Enterprise AI Agents shows how to extend their value by wiring structured data to AI.
With well-prepared metadata, business definitions, and operating workflows, AI can understand how your organization describes customers, products, sales, claims, time periods, regions, and performance. Your team can ask questions in everyday language, explore the data, compare results, identify patterns, and turn records into useful business information.
This book guides you through the complete journey from a business question to a reviewed answer. In simple easy to understand language, Viren Shah explains:
- The different shapes of structured data and how AI works with each one.
- How an AI model reads tables, columns, relationships, and metadata.
- How text-to-SQL turns a natural-language question into a database query.
- How business definitions, mappings, examples, and operating knowledge give data its full meaning.
- How permissions, validation, traceability, and human review support trustworthy answers.
- How focused AI agents can bring natural-language analysis into recurring business workflows.
- How technical knowledge, business knowledge, and AI capabilities come together in an enterprise system.
The book is written for data professionals, business operators, executives, and business leaders.
Data professionals will see how databases, metadata, governance, and AI workflows connect. Business operators will see how their practical knowledge can guide the way AI interprets data. Executives will gain a clear view of the architecture, people, information, and investments that support enterprise AI.
Building Enterprise AI Agents presents a practical opportunity: build on the databases, dashboards, reports, and business systems your organization already uses, then create a natural-language path to the information inside them.
The result is a shared vision of an enterprise where more people can reach the data they need, ask richer questions, perform meaningful analysis, and use trusted information to move the business forward.
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