Use Cases
Real-world AI Agent use cases from marketing to engineering, research to productivity — with recommended tool stacks and step-by-step guides
8
Marketing
14
Engineering
7
Research
14
Productivity
8
Industry
Batch Paper Abstract Extraction + Comparative Analysis
Upload multiple PDF papers, then let the AI Agent automatically extract abstracts, research methods, and key findings, and generate a comparative analysis table to help researchers quickly grasp field progress.
Steps
- 1.Upload PDFs to a designated folder
- 2.Configure filesystem MCP to read files
- 3.Let AI extract key information and structure it
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Competitor Product Analysis
Let the Agent systematically analyze competitors' product features, pricing strategies, user reviews, and market positioning to generate a comprehensive competitive analysis report to support product decisions.
Steps
- 1.List target competitors
- 2.Agent automatically visits official websites, App Store reviews, and social media
- 3.Analyze product feature matrix and differentiation advantages
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Investment Due Diligence Report Automation
Enter the target company name, and the AI Agent automatically searches for company background, funding history, founding team, competitive landscape, and industry position, generating a professional investment due diligence report in 30 minutes, replacing 2-3 days of work for junior analysts.
Steps
- 1.Enter the target company name and research focus areas
- 2.Agent automatically searches the company website, Crunchbase, and LinkedIn
- 3.Analyze funding rounds, valuation trends, and investors
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Personalized Study Plan + AI Exercise Generator
Students input their learning goals (e.g., 'Pass the PMP exam in 30 days') and current knowledge level. The AI Agent automatically generates a personalized study plan: breaking down knowledge points, recommending resources, arranging daily tasks, and dynamically adjusting difficulty based on each practice session's results. Weak areas are automatically reinforced, functioning as a 24/7 private AI tutor.
Steps
- 1.Collect student information: target exam, current level, daily available study time
- 2.AI breaks down the exam syllabus and generates a knowledge point map with priorities
- 3.Push daily learning tasks and corresponding resources
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