research-ops

To gather current evidence for market recommendations, use an evidence-first research workflow that selects the lightest search lane first, escalates for synthesis when multiple sources are needed, and labels sourced facts separately from inference. This ensures decision-ready outputs with freshness-by-date reporting.

The best way to enrich company leads is by enforcing clear evidence boundaries that label sourced facts, user-provided context, inference, and recommendations separately. This prevents mixing claims and produces structured results suitable for lead intelligence and comparative analysis.

Evidence synthesis handles recurring research by flagging tasks that should become monitored research instead of repeated one-off lookups. The workflow evaluates whether a question requires ongoing monitoring and recommends setting up a recurring research monitor.

Yes, you can use current events research for comparative analysis by providing user context and notes alongside public sources. The workflow orchestrates evidence gathering across search lanes while enforcing labeled evidence boundaries and freshness-by-date reporting.

You should escalate from a lightweight search lane to deep research when multiple sources are needed for evidence synthesis. The workflow starts with the lightest execution first, then escalates to deeper research lanes like market-research or lead-intelligence when comparative analysis requires more comprehensive data.

Yes, the evidence-first research workflow operates without external dependencies by orchestrating across internal search lanes like exa-search, deep-research, and market-research. It produces current-state findings and recommendations from public sources plus user-provided context using lightweight-first execution.