AI Autonomous Research Engine
Iterative deep research with cited reports
Description
AI Autonomous Deep Research Engine, inspired by Karpathy's AutoResearch project. It employs a multi-round autonomous iterative research loop: gather information, analyze and verify, self-assess on five dimensions, identify blind spots, and target improvements, iterating until the report meets standards. Supports scenarios such as market research, competitive analysis, technology selection, industry reports, and academic reviews, automatically adapting to 3-8 rounds of research depth. Outputs a visual HTML report with cited sources, including core findings, comparison matrix, scoring radar chart, and actionable recommendations. Each round outputs a progress summary, making the research process transparent. Suitable for creators, entrepreneurs, and researchers who need in-depth understanding of a domain and data-driven decision-making.
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Research Report Generator
📝 Value in one sentence: Enter a topic or upload materials, and AI handles the entire process from organizing sources to drafting. 🔍 Core features: Smart source integration: Upload multiple documents and AI automatically extracts key viewpoints, critical data, and representative cases, while removing duplicates and flagging conflicts. Automatic outline generation: Based on the topic or source content, it creates a logically clear and well-structured article outline. One-click draft writing: Generates content section by section according to the outline, with every data point and case study source-tagged and traceable. Five writing styles: Supports formal reports, WeChat articles, Xiaohongshu notes, academic papers, and business briefings. Transparent citations: Every figure and viewpoint is marked with its source—no fabrication or invention. Automated content workflow: Source parsing → viewpoint extraction → outline generation → writing in five styles. 🎯 Use cases: 📊 Industry research: Enter "Humanoid Robot Industry 2026" to generate a draft analysis report with data and case studies. 📝 Content creation: Upload 3 related articles to combine into an in-depth WeChat article. 📚 Academic writing: Upload multiple paper abstracts to create a literature review draft. 📋 Competitor analysis: Upload several competitor documents to instantly generate a comparative analysis report. 🧠 Personal learning: Enter a new-domain topic to quickly generate a knowledge overview. 💼 Business decisions: Input business data and background information to produce a decision brief for the CEO. 👩💼 Who it's for: Researchers, analysts, content creators, product managers, students, and consultants—anyone who needs to quickly produce high-quality first drafts.
Deep Stock Research Engine
Not a news summary, but an individual stock research report with a methodological framework. Enter a company (A-share/H-share/US stock name or code), and it will perform 10-15 bilingual web searches to produce a report based on a seven-dimension framework: ① Business Model – where money comes from and goes, with a "translated into plain language" version ② Revenue Structure – breakdown by business, growth engines and drags ③ Moat – mandatory answer on widening or narrowing, using market share, gross margin, and pricing power ④ Financial Quality – cash flow vs profit alignment, changes in receivables, inventory, and goodwill ⑤ Competitive Landscape – competitor comparison table and concentration direction ⑥ Valuation Framework – only data and calculation framework, no judgment of over/undervaluation ⑦ Risk List – sorted by impact, each with verifiable trigger signals Each report includes: a one-page bull/bear summary (with substantial evidence on both sides), a next-quarter tracking list, and data sources for each point. Three iron rules: · Each key number is traceable to official filings or authoritative media; if not found, labeled 'insufficient information', never fabricated · Facts, calculations, and inferences are labeled separately · No stock price predictions, no target prices, no buy/sell advice – even for 'should I buy', only bull/bear evidence is given Supports three perspectives: Understand the Business (default), Financial Checkup, and Company Comparison. Suitable for investment researchers, financial content creators, and serious investors who want to systematically understand a company.
Research Report AI v4.2
Automatically generate professional research reports with intelligent data collection, deep web research, and structured writing. ✅ Three-stage checkpoint system ✅ Dynamic research dimensions (3-7) ✅ Actionable quality self-checks ✅ Iterative optimization support. Ideal for thematic research, project studies, field investigations, policy evaluations, and other official document writing tasks.
AI Autonomous Research Engine
Iterative deep research with cited reports
Description
AI Autonomous Deep Research Engine, inspired by Karpathy's AutoResearch project. It employs a multi-round autonomous iterative research loop: gather information, analyze and verify, self-assess on five dimensions, identify blind spots, and target improvements, iterating until the report meets standards. Supports scenarios such as market research, competitive analysis, technology selection, industry reports, and academic reviews, automatically adapting to 3-8 rounds of research depth. Outputs a visual HTML report with cited sources, including core findings, comparison matrix, scoring radar chart, and actionable recommendations. Each round outputs a progress summary, making the research process transparent. Suitable for creators, entrepreneurs, and researchers who need in-depth understanding of a domain and data-driven decision-making.
Related Skills
View allResearch Report Generator
📝 Value in one sentence: Enter a topic or upload materials, and AI handles the entire process from organizing sources to drafting. 🔍 Core features: Smart source integration: Upload multiple documents and AI automatically extracts key viewpoints, critical data, and representative cases, while removing duplicates and flagging conflicts. Automatic outline generation: Based on the topic or source content, it creates a logically clear and well-structured article outline. One-click draft writing: Generates content section by section according to the outline, with every data point and case study source-tagged and traceable. Five writing styles: Supports formal reports, WeChat articles, Xiaohongshu notes, academic papers, and business briefings. Transparent citations: Every figure and viewpoint is marked with its source—no fabrication or invention. Automated content workflow: Source parsing → viewpoint extraction → outline generation → writing in five styles. 🎯 Use cases: 📊 Industry research: Enter "Humanoid Robot Industry 2026" to generate a draft analysis report with data and case studies. 📝 Content creation: Upload 3 related articles to combine into an in-depth WeChat article. 📚 Academic writing: Upload multiple paper abstracts to create a literature review draft. 📋 Competitor analysis: Upload several competitor documents to instantly generate a comparative analysis report. 🧠 Personal learning: Enter a new-domain topic to quickly generate a knowledge overview. 💼 Business decisions: Input business data and background information to produce a decision brief for the CEO. 👩💼 Who it's for: Researchers, analysts, content creators, product managers, students, and consultants—anyone who needs to quickly produce high-quality first drafts.
Deep Stock Research Engine
Not a news summary, but an individual stock research report with a methodological framework. Enter a company (A-share/H-share/US stock name or code), and it will perform 10-15 bilingual web searches to produce a report based on a seven-dimension framework: ① Business Model – where money comes from and goes, with a "translated into plain language" version ② Revenue Structure – breakdown by business, growth engines and drags ③ Moat – mandatory answer on widening or narrowing, using market share, gross margin, and pricing power ④ Financial Quality – cash flow vs profit alignment, changes in receivables, inventory, and goodwill ⑤ Competitive Landscape – competitor comparison table and concentration direction ⑥ Valuation Framework – only data and calculation framework, no judgment of over/undervaluation ⑦ Risk List – sorted by impact, each with verifiable trigger signals Each report includes: a one-page bull/bear summary (with substantial evidence on both sides), a next-quarter tracking list, and data sources for each point. Three iron rules: · Each key number is traceable to official filings or authoritative media; if not found, labeled 'insufficient information', never fabricated · Facts, calculations, and inferences are labeled separately · No stock price predictions, no target prices, no buy/sell advice – even for 'should I buy', only bull/bear evidence is given Supports three perspectives: Understand the Business (default), Financial Checkup, and Company Comparison. Suitable for investment researchers, financial content creators, and serious investors who want to systematically understand a company.
Research Report AI v4.2
Automatically generate professional research reports with intelligent data collection, deep web research, and structured writing. ✅ Three-stage checkpoint system ✅ Dynamic research dimensions (3-7) ✅ Actionable quality self-checks ✅ Iterative optimization support. Ideal for thematic research, project studies, field investigations, policy evaluations, and other official document writing tasks.
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