Lilly Tech Systems
Enterprise Search with AI
Build intelligent search systems that understand meaning, not just keywords — from semantic search and hybrid retrieval to personalization, analytics, and production best practices.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
Why traditional search fails in the enterprise, and how AI transforms information retrieval.
2. Semantic Search
Vector embeddings, similarity search, embedding models, and vector database integration.
3. Hybrid Search
Combining keyword and semantic search with reciprocal rank fusion and learned ranking.
4. Personalization
User context, behavioral signals, role-based ranking, and personalized search experiences.
5. Analytics
Search quality metrics, click-through analysis, query understanding, and continuous improvement.
6. Best Practices
Indexing strategies, relevance tuning, scaling search infrastructure, and operational excellence.
What You'll Learn
By the end of this course, you'll be able to:
Semantic Understanding
Build search systems that understand meaning and intent, not just keyword matching.
Hybrid Retrieval
Combine lexical and semantic search for optimal relevance across diverse content types.
Personalization
Deliver personalized search results based on user context, behavior, and organizational role.
Search Analytics
Measure and improve search quality with metrics, A/B testing, and continuous feedback loops.