tech-search

To generate a deep tech research report, input a natural-language query. The system decomposes it into searchable sub-queries, performs parallel web searches, and synthesizes evidence into structured documentation with source quality signals.

The best way to compare technologies is using a structured research pipeline that runs parallel web discovery, extracts technical facts and code examples, and synthesizes evidence into a consolidated report with coverage evaluation and next-step recommendations.

Evidence evaluation works by applying coverage evaluation with stop/continue logic during web extraction. It assesses source quality signals and synthesizes extracted technical facts to determine if enough evidence exists to conclude the deep research.

Yes, you can use parallel web fetch and search for expert-level technology investigation. The system searches multiple angles simultaneously, deep-reads relevant sources, and fits scenarios requiring consolidated findings and best-practice documentation.

The generated technical research documentation follows a structured format saved to docs/research/{YYYY-MM-DD}-{slug}/, containing an index, query context, extracted prompt, full report, and next-step recommendations.

No, you do not need manual web digging to produce evidence-based technical documentation. The pipeline automates query decomposition, parallel web discovery, structured extraction, and synthesis into a self-contained research report.