websearch-deep

Deep research uses problem decomposition to break complex questions into 3-5 sub-questions, then generates 3-5 query variations per sub-question to gather comprehensive evidence. Sources are ranked, synthesized with numbered citations, and iteratively refined up to 5 times to reach completeness and evidence transparency.

Structured research decomposes the decision into sub-questions, searches multiple angles per question, ranks and synthesizes source evidence with citations, then iteratively refines findings. This methodology produces a verification artifact documenting the research execution and evidence basis for your choice.

Yes. Multi-query deep research applies to multi-domain investigations by decomposing strategic questions, generating varied queries for each sub-question, synthesizing ranked evidence, and refining iteratively. The approach supports technology selection, architecture decisions, and comparative analyses requiring cross-domain synthesis.

Evidence synthesis with numbered citations documents source rankings and reasoning at each step. Iterative refinement up to 5 times strengthens weak areas, and a verification artifact records the full research execution, source evaluation, and synthesis logic for reproducibility and transparency.

Clarify your complex question and identify its domain scope. Deep research works best when the core question is decomposable into 3-5 sub-questions; no special tools or environment are required. The methodology handles problem breakdown, query generation, evidence synthesis, and iterative refinement from there.

Deep research suits complex, multi-domain questions requiring evidence synthesis and citation transparency. It may be overkill for simple factual lookups or single-domain queries with obvious answers. Use it when you need comprehensive cross-domain synthesis, strategic comparison, or architecture justification.