9. Research & Analysis

Initiates research projects using coordinated AI agents for efficient information gathering and analysis.

Provides expert review of PhD-level academic manuscripts and research proposals for scholarly rigor and quality.

Guides PhD-level systematic literature reviews per PRISMA standards, covering protocol development, search optimization, screening, and data extraction.

Analyzes user experience research (UXR) report PDFs to extract key findings, recommendations, and strategic connections for business decision-making.

Analyzes customer interview transcripts to extract themes, summaries, key quotes, topics, and timestamps for structured insights and chapter creation.

Enables reliable web content extraction and search when standard tools fail due to access restrictions, rate limits, or validation errors.

Provides a structured methodology for conducting rigorous, evidence-based research with traceable sources, quality gates, and intelligence tradecraft standards.

Conducts deep company research to create comprehensive dossiers for job applications, interviews, and cultural fit assessments.

Automates collection and analysis of job market data, including sector trends, salary benchmarks, and skills demand for strategic business insights.

Extracts key contributions, methods, and contextual findings from research papers (PDFs, DOIs, URLs) to create structured summaries for researchers.

Applies systematic research methodology for multi-step fact-finding, web search, and information synthesis using Brave Search and Puppeteer.

Assesses logical flow, structure, readability, and quality of research paper text targeting top-tier computer science conferences.

Automates comprehensive review of computer science research papers, identifying weaknesses, structural flaws, and missing evidence for conference submissions.

Provides Jobs-to-be-Done and psychographic research frameworks to inform brand positioning, messaging, and strategy through customer motivation analysis.

Applies structured analytical frameworks across artifacts like code, documents, and systems, featuring adversarial review and post-plan validation.

Analyzes proposed changes for impact on existing systems, identifying breaking changes, dependencies, and risks to support safe brownfield project modifications.

Provides a structured methodology for step-by-step problem-solving, including decomposition, hypothesis verification, and adaptive revision to tackle complex and ambiguous challenges.

Applies structured technical research methodology (YAGNI, KISS, DRY) for technology evaluation, architecture analysis, and solution design.

Uses a three-round iterative strategy with parallel subagents to systematically explore and analyze complex, multi-faceted topics.

Conducts deep, iterative web searches using parallel queries and failure learning to efficiently gather technical research, documentation, and code examples.

Analyzes conversation history to identify key learnings, patterns, and techniques, then proposes skill updates with preview before implementation.

Automates deep research using Exa AI's neural search for content retrieval and information gathering.

Generates comprehensive research reports by autonomously querying the web and synthesizing information using LLMs and search APIs.

Automates multi-step research with citations using OpenAI's Deep Research API, leveraging o3/o4 models for comprehensive information gathering.