GenAI-powered search often breaks down due to misaligned queries, weak relevance signals, and unobserved failure paths. Without systematic tuning, teams struggle to improve recall and relevance without introducing new dead ends.
To win, your GenAI search solutions must be continuously recalibrated using real usage signals and aligned to how users actually search.
When GenAI search optimization is reactive or incomplete, search quality plateaus quickly:
- Pipeline drift: Search pipelines fail to reflect real user behavior captured in logs and interaction data.
- Relevance gaps: Ranking and scoring models surface plausible but incorrect results for complex queries.
- Search failures: Users hit dead ends or empty responses in multi-step or ambiguous query paths.
These issues reduce trust, increase abandonment, and undermine the value of GenAI search experiences.
In this hands-on workshop, your team systematically improves GenAI search quality using user data, relevance tuning, and failure analysis.
- Recalibrate search pipelines using insights derived from real user logs and query patterns.
- Optimize relevance ranking and scoring to better reflect user intent and success signals.
- Align search queries with user context to improve precision and reduce irrelevant results.
- Improve recall in complex or multi-hop query paths.
- Identify and reduce dead ends and query failures through targeted analysis and tuning.
- Recalibrating Search Pipelines with User Logs
- Optimizing Relevance Ranking and Scoring
- Aligning Search Queries with Use Context
- Improving Recall in Complex Query Paths
- Reducing Dead Ends and Query Failures
- Diagnose where and why GenAI search is failing real users.
- Improve relevance and recall using evidence from usage data.
- Align search behavior more closely with user context and intent.
- Reduce failed queries and dead ends across complex search journeys.
- Establish a repeatable process for continuously tuning GenAI search quality.
Who Should Attend:
Solution Essentials
Facilitated workshop (in-person or virtual)
4 hours
Intermediate
Search pipelines, user log samples, relevance scoring artifacts, and guided tuning exercises