Semantic and hybrid search: Stop making users guess the right keywords. Users know what they want, but they don’t always know the exact title, phrase, or keyword your search system expects.

Traditional keyword search works when the query matches your data. When users describe an idea differently, use a synonym, or search by intent, relevant results can disappear. Semantic search improves recall, but relying on meaning alone can introduce noise and miss the exact terms that matter.

In this hands-on session, learn how to balance keyword precision with semantic understanding to deliver faster, more relevant search results across different query styles.

• Match exact terms: Use full-text search when titles, product IDs, legal terms, or specific phrases need to be found precisely.
• Understand user intent: Retrieve relevant results even when users phrase a query differently or don’t know the right keywords.
• Reduce irrelevant results: Combine lexical and semantic signals to balance precision and recall.
• Prepare search for production: Tune weighting, filters, ranking, and retrieval strategies based on your users, data, and latency requirements.

In this live demo we compare full-text, semantic, and hybrid search, and see how to build and tune each approach with Redis.