DeepTrace systematically explores web content, builds structured question trees, and delivers verified research outputs—eliminating AI uncertainty and shallow browsing limitations.
Most tools skim surface-level content without deep inspection, missing critical context and nuance essential for accurate research.
Traditional systems often refuse to visit certain URLs or stop prematurely, leaving gaps in research coverage and verification.
AI-based tools produce inconsistent results across runs, making replication and verification of research findings impossible.
DeepTrace is a CLI-based research engine that approaches web exploration methodically. It generates structured question trees, inspects multiple web pages deterministically, stores verified data as clean JSON, and produces synthesized research outputs.
Built for power users who need precise control over research parameters and workflows.
Automatically decomposes research topics into logical question trees for systematic exploration.
Visits and analyzes web pages consistently, ensuring reproducible research outcomes.
All verified information is stored as structured JSON, ready for analysis or integration.
Academic professionals needing verifiable, reproducible web research for papers and studies.
Business professionals requiring comprehensive market research and competitive analysis.
Individuals conducting deep-dive investigations who need systematic evidence collection.
Users provide a research topic through the command-line interface, specifying scope and parameters.
The engine decomposes the topic into structured questions, creating a logical exploration path.
Systematically visits relevant web pages, extracting and verifying information according to the question tree.
All verified findings are stored as clean JSON with source attribution and confidence scoring.
Produces comprehensive research reports combining all verified data into actionable insights.