multi-agent-research

Orchestrating parallel agents involves classifying a complex research question, planning specific subtasks, delegating them to subagents, and synthesizing the findings. This mechanism enables comprehensive cross-domain analysis and multi-perspective reporting.

Multi-agent research is a workflow that distributes research tasks across parallel subagents to gather and compare diverse sources. You need it for topics requiring breadth or depth analysis, cross-domain perspectives, and comprehensive reporting.

Synthesizing findings from multiple agents combines their parallel outputs into a single comprehensive report. The synthesis includes source attribution and assigns confidence levels to the consolidated information for transparent reporting.

Yes, you can use parallel subagents to compare technologies across different perspectives. Running a query to compare topics triggers a full multi-agent research workflow that tackles the breadth and depth of the analysis efficiently.

No external dependencies are required to run multi-agent research workflows. The orchestration operates independently using its internal scripts to classify, plan, delegate, and synthesize distributed research tasks.