Choose the right experience
Not every search needs a generated paragraph. Sometimes a clear route to a source is the better output.
AI Search Engine / Discover with AI
More useful answers.
More visible evidence.
Explore AI search as three distinct jobs: discovering sources, retrieving relevant evidence, and generating an answer within that evidence.
Fluent output is not the same as a supported answer.
Choose whether the user needs a direct destination, a collection of sources, or a synthesized explanation. Preserve source identities and dates, define freshness by task, and evaluate what happens when evidence is incomplete or contradictory. Let uncertainty be a visible outcome rather than a hidden failure.
Evaluate the stages
Inspect discovery, passage selection, answer support, and citation accuracy separately.
Keep the reader in control
Place limitations next to the affected claims and make supporting sources easy to inspect.
This is a guide to AI search design. The local examples do not call a model or generate live answers.
KEEP EXPLORING
Connect the next part of your workflow.
AI search engines: from discovery to evidence-backed answers
Separate discovery, retrieval, and generation. Design an AI search experience that makes its evidence and limitations visible.
Read the full guideSearch Engine LLM
Turn search results into small, inspectable evidence packets for a large language model—without treating retrieved text as instructions.
Explore the topicSearch Engine API
Explore how a search engine API turns discovery into structured data—and choose the source that fits the question your application needs to answer.
Explore the topicYOUR NEXT IDEA STARTS HERE
A little search data.
A whole lot of possibility.
Explore the patterns, understand the tradeoffs, and build from a clearer starting point.