Multi-Agent Deep Research

Open-ended market research questions need planning, specialized evidence gathering, and synthesis — a single-prompt LLM call produces unsourced, unstructured answers.

Supervisor plans the research question and dispatches category-specific workers; workers gather live search evidence (Tavily), extract structured findings with Pydantic schemas, and score source quality; a synthesis step writes a deterministic report plus structured source metadata, with resilient no-API fallback paths.

• Implemented supervisor/worker orchestration, live search, structured extraction, source-quality scoring, deterministic report synthesis, and no-API fallbacks.

• Structured extraction with schema validation is what turns agent output from prose into data you can rank and audit.