deep-research

Multi-source research on complex topics uses a tree-like exploration pattern to decompose questions into focus areas, launch parallel sub-agent research, evaluate source credibility, and synthesize findings into a structured report with proper citations.

Parallel sub-agent research decomposes complex questions into thematic focus areas and launches concurrent research streams. It cross-references critical claims across multiple evaluated sources to organize findings thematically for structured reporting.

Source evaluation during a deep dive assesses each reference for credibility across five criteria: authority, currency, objectivity, accuracy, and coverage. This ensures that information synthesis relies on vetted, high-quality sources.

Yes, deep research on complex topics requires parallel processing capabilities to execute its tree-like exploration pattern. It systematically decomposes subjects and launches parallel sub-agents regardless of the specific topic domain.

Automated structured research acknowledges limitations within the final report. While it evaluates source credibility and cross-references claims, the synthesized findings depend entirely on the availability and accuracy of the accessed multi-source data.