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Course Overview
- Spotter Architecture
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Spotter Architecture Part 1 6 min
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Spotter Architecture Part 2 5 min
- Review
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Review
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Knowledge Check 5 min
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Feedback 5 min
This course introduces you to how Spotter, ThoughtSpot’s natural language query engine, works behind the scenes to deliver fast, accurate, and explainable results. You’ll begin by exploring Spotter’s multi-layered architecture, including key components such as Retrieval-Augmented Generation (RAG), the BARQ reasoning layer, PromptIQ, and the AI Trust Layer. These systems work together to understand user intent, enrich prompts with business context, and maintain data security throughout the query process. In the second part of the course, you'll learn how Spotter translates LLM output into trusted search tokens, executes queries against the data warehouse, and returns personalized visual responses. By the end, you’ll gain a clear understanding of how ThoughtSpot blends AI with enterprise-grade architecture to power natural language search at scale.
This course includes video lessons, an interactive review, and concludes with a knowledge check. While the knowledge check is not graded, it is designed to help you assess your understanding of the key concepts covered.