deep-research

Multi-source analysis on complex topics is conducted by decomposing the main question into distinct focus areas like market, technology, and policy, then running parallel sub-agent research to synthesize structured findings with proper citations.

The best way to structure comprehensive research reports is by systematically gathering information into distinct focus areas such as infrastructure and consumer economics, synthesizing data from parallel research into a holistic view with citations.

Yes, you can use parallel sub-agent research to decompose complex questions into distinct focus areas, enabling thorough multi-source analysis and delivering structured reporting with proper citations.

Deep research requires no external dependencies to generate structured reporting, but it does require parallel execution capabilities to systematically gather and synthesize information from multiple angles into cited findings.

You need to decompose a research question into distinct focus areas when a topic requires comprehensive, multi-source analysis to understand overlapping aspects like market, technology, and policy for a holistic view.

Automated parallel sub-agents for complex topic research are limited to the scope of decomposed focus areas defined during query processing, meaning highly nuanced or deeply interconnected niche subjects may require manual synthesis beyond the structured report.