An Introduction to GenAI Data Retrieval Best Practices
Enterprise GenAI retrieval introduces challenges around context modeling, metadata design, and measurement that directly affect answer quality and application behavior. This workshop introduces core retrieval practices and how they connect to real application outcomes.
To win, your teams must implement retrieval approaches that model document context correctly, embed with precision, and measure retrieval effectiveness using clear KPIs.
When GenAI retrieval practices are immature, teams encounter predictable issues:
- Unclear retrieval foundations: Lack a shared understanding of enterprise GenAI retrieval concepts and how they differ from basic search.
• Poor application alignment: Retrieval strategies are disconnected from application experience, leading to irrelevant or incomplete responses.
• Low precision and visibility: Documents are embedded without structured context, metadata, or measurable indicators of retrieval quality.
These gaps lead to unreliable answers, degraded application experiences, and limited ability to improve retrieval over time.
In this hands-on workshop, your team builds a practical foundation for enterprise GenAI retrieval through guided concepts and applied exercises.
- Introduce core enterprise GenAI retrieval concepts and how they apply to production environments.
• Analyze how retrieval behavior directlyimpacts application experience and user-facing results.
• Model document contexts and sections to improve relevance during retrieval.
• Apply metadata strategies during embedding to increase precision and control.
• Define and evaluate KPIs that measure retrieval effectiveness and guide improvement.
Introducing Enterprise GenAI Retrieval Concepts
Linking Retrieval with Application Experience
Modeling Document Contexts and Sections
Embedding with Metadata for Precision
Defining KPIs for Retrieval Effectiveness
• Understand foundational enterprise GenAI retrieval concepts and terminology.
• Connect retrieval design decisions to downstream application experience.
• Structure documents and sections to improve retrieval relevance.
• Apply metadata during embedding to support more precise results.
• Define KPIs that make retrieval quality measurable and actionable.
Who Should Attend:
Solution Essentials
Virtual or in-person
2 hours
Introductory; familiarity with GenAI or search concepts recommended
GenAI retrieval frameworks, embedding workflows, and example datasets