Give an agent a goal instead of a query. It plans, retrieves, analyzes, synthesizes and reports — and you can watch every stage, interrupt it, or fork it into a new direction.
An agent is only useful in research if its work can be inspected. Autonomy without observability produces confident output nobody can check.
SearchPilot exposes the agent's plan, its source picks, its intermediate analysis, and its final synthesis as separate, reviewable artifacts.
Each stage streams as it completes, so you can course-correct early rather than discovering a bad framing at the end.
Split a broad question across several agents — one per market, competitor, or region — and merge their findings into a single comparative brief.
Approve the plan, drop a source, tighten the scope, or re-run one stage without restarting the entire investigation.
What are AI research agents?
AI research agents are goal-directed systems that plan and execute a multi-step research process — retrieval, evaluation, analysis and reporting — with limited human input between steps.
How are agents different from a single AI query?
A query returns one answer from one retrieval pass. An agent maintains state across many steps, adapts its plan based on what it finds, and produces a compound deliverable.
Can I supervise what an agent does?
Yes. SearchPilot renders each stage as it happens, so you can approve the plan, edit the source set, or stop a run before it commits to a weak framing.
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