deep-research

Triangulate research claims by scoring source credibility from 0-100 and cross-verifying major points across 3+ sources. This validation mechanism ensures enterprise analyses remain accurate and decision-makers can trust the synthesized results.

Structure executive summaries using the automated packaging phase, which refines critiqued data into local reports. It handles progressive context management to condense complex topics into structured, citation-backed bibliographies without external dependencies.

Run autonomous research locally using a self-contained Python-based engine. It executes the entire workflow, from scoping to packaging, and stores generated reports locally, ensuring complete operation without requiring external dependencies.

Deep research supports mode-based depth with quick, standard, deep, and ultradeep options. You can select a mode to balance retrieval speed and verification rigor for enterprise tasks like risk assessment, competitive intelligence, or technical due diligence.

Cross-source triangulation matters because it validates major claims across multiple independent references, reducing the risk of relying on biased or inaccurate data. This rigorous verification is crucial for producing credible policy analysis and technical due diligence reports.