Building search in the age of generative AI: A blueprint for success
There’s never been a better time to create exceptional search experiences. By leveraging the capabilities of LLMs and generative AI, we can predict user intent, improve relevance, surface timely content, and even provide human-like responses.
But one size doesn’t fit all for search. You can utilize out-of-the-box technology, build your own with feature-rich, custom design and functionality, or anything in-between.
Discover the blueprint for planning, designing, and building a search experience that meets your users’ needs, your team’s resources, and (of course) your budget. With an overview of the latest tech and real-world case studies that highlight what’s possible, you can envision your future search experience and bring it to life.
Highlights
- See how top companies are incorporating AI-driven enterprise search architecture to drive user engagement
- Discover the options for integrating generative AI and LLMs into your search function
- Get an overview of optimal data ingestion and enrichment practices for search
- Understand how to mitigate concerns surrounding privacy, observability, and monitoring to gain organizational buy-in
Additional resources
- What is generative AI?
- What is a large language model?
- Choosing an LLM: The 2024 getting started guide to open-source LLMs
- 5 AI search trends impacting developers in 2024
- See how a vector database is your starting point for powering AI search
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