Build a web research agent
A source-backed research pipeline that searches, browses, extracts, synthesizes, and remembers.
Agents that need current, verifiable information from the web.
A concise answer with traceable sources, structured evidence, and reusable memory.
Tool chain
How the agent completes the task
- 1
Discover sources
Web searchRun broad and semantic searches, then keep a diverse shortlist of promising sources.
InputResearch question, freshness window, source constraints
OutputRanked URLs with snippets and relevance signals
Fallback: Retry with a second provider and simpler keyword queries.
- 2
Inspect interactive pages
Browser automationOpen pages that require JavaScript or interaction and capture the relevant state.
InputCandidate URLs and the evidence to locate
OutputRendered pages, action results, and page snapshots
Recommended tool
BrowserbaseHeadless browser infrastructure built for AI agentsFallback: Skip browser execution when a clean text representation is available.
- 3
Extract clean evidence
Web extractionConvert selected sources into structured, model-ready content with source locations intact.
InputSelected source URLs or browser snapshots
OutputClean text or JSON with source metadata
Fallback: Use a reader endpoint, then fall back to targeted DOM extraction.
- 4
Store reusable context
Memory and retrievalPersist verified findings and retrieval metadata for follow-up questions.
InputVerified findings, citations, entities, and research scope
OutputSearchable memories linked to their original sources
Recommended tool
Mem0Universal memory layer for AI agents — persistent, personalized recall across sessionsFallback: Return the final evidence bundle even when durable memory is unavailable.
