deep-research

To generate a cited market research report, you need a tool that builds targeted search queries, reads credible web sources iteratively, and synthesizes the evidence into a structured Markdown document with source attributions. This automates gathering and comparing scattered information into cited findings.

Deep research differs from a single web search lookup by requiring iterative query generation, source evaluation, and recursive follow-up exploration. Instead of relying on one lookup, it synthesizes evidence from multiple real web sources to produce a structured report with cited findings for complex questions like market sizing.

Yes, you can use this approach for competitor analysis, market sizing, and payment ecosystem research. It investigates topics by gathering and comparing evidence from multiple real web sources, validating deeper questions before you make a decision, and returning a structured Markdown report with cited sources.

To synthesize evidence from multiple web sources, the process distills findings into concise learnings with source attribution. By building targeted search queries, reading credible sources, and following up on unanswered questions, it turns scattered information into a structured Markdown report with a sources section.

The best way to investigate diaspora e-commerce trends is to use an iterative research process that builds targeted search queries, evaluates credible sources, and follows up recursively. This synthesizes scattered information into a structured Markdown report with cited findings and a dedicated sources section.

You need iterative query generation for web research when a question requires deeper validation than a single lookup, such as analyzing payment options or competitor scans. It enables recursive follow-up exploration and source evaluation to synthesize evidence into a structured, cited Markdown report.