Datapilot V1
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Datapilot V1
The AI Company & Topic Researcher is a sophisticated web scraping and analysis tool designed for competitive intelligence, market research, and technical deep dives. It automates the entire research pipeline from data collection to AI-powered strategic analysis.
Pricing
from $0.01 / 1,000 results
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Developer
Satyam Gupta
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10 months ago
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🧠 AI Company & Topic Researcher
📋 Table of Contents
- Overview
- Key Features
- Installation
- Usage
- Input Schema
- Output Schema
- Research Modes
- Technical Stack
- Examples
- Troubleshooting
🎯 Overview
The AI Company & Topic Researcher is a sophisticated web scraping and analysis tool designed for competitive intelligence, market research, and technical deep dives. It automates the entire research pipeline from data collection to AI-powered strategic analysis.
What Makes It Unique?
- Dual Research Modes: Switch between company analysis and general topic research
- Multi-Source Aggregation: Combines official websites, news, reviews, social mentions, and competitive data
- AI-Powered Insights: Uses Groq's Llama 3.3 70B model for deep strategic analysis
- Structured Output: Generates SWOT analysis, pricing strategies, market positioning, and actionable recommendations
- Zero Configuration: Works out-of-the-box with sensible defaults
🚀 Key Features
🔍 Intelligent Web Scraping
- Smart URL Discovery: Automatically finds and categorizes important pages (pricing, features, about, blog, etc.)
- Static & Dynamic Content: Handles both traditional HTML and JavaScript-rendered content
- Multi-Page Extraction: Scrapes homepage, pricing, features, documentation, blog posts, and more
- Anti-Detection: Uses realistic browser fingerprints and human-like behavior patterns
📊 Comprehensive Data Collection
Company Analysis Mode
✅ Official website content and metadata
✅ Pricing tiers and monetization models
✅ Product features and capabilities
✅ News articles and press releases
✅ Customer reviews from G2, Trustpilot, Capterra, Product Hunt
✅ Social media mentions (LinkedIn, Twitter/X, Reddit)
✅ Competitor identification and analysis
✅ Blog posts and content marketing insights
General Topic Research Mode
✅ Top authoritative sources discovery
✅ Technical documentation and guides
✅ Recent developments and news
✅ Community discussions and sentiment
✅ Implementation examples and use cases
🤖 AI-Powered Analysis
The actor uses Llama 3.3 70B Versatile via Groq API to generate:
For Companies:
- Company Overview (description, industry, target market, value proposition)
- Product Analysis (core products, key features, technology stack)
- Pricing Strategy (pricing model, positioning, monetization)
- Market Position (market strength, brand reputation, growth trajectory)
- Competitive Landscape (main competitors, threats, differentiation)
- Customer Sentiment (overall sentiment, praise/complaints, NPS)
- SWOT Analysis (top 5 strengths, weaknesses, opportunities, threats)
- Strategic Insights (growth potential, investment worthiness)
- Risk Assessment (risk score 0-100, key risk factors)
- Executive Summary (4-6 paragraph comprehensive overview)
For Topics:
- Topic Overview (definition, key concepts, importance)
- Technical Deep Dive (how it works, core components, architecture)
- State of the Art (current trends, recent advancements, leading players)
- Pros & Cons (advantages, disadvantages, implementation challenges)
- Use Cases (real-world applications across sectors)
- Future Outlook (predictions, research directions, disruption potential)
- Learning Resources (prerequisites and next steps)
📥 Installation
Prerequisites
- Python 3.11+
- Apify Account (for running as an Actor)
- Groq API Key (optional, fallback provided)
Option 1: Run on Apify Platform (Recommended)
- Import the Actor to your Apify account
- Configure inputs via the Apify Console
- Run and view results in the dataset
Option 2: Local Development
# Clone the repositorygit clone https://github.com/yourusername/ai-company-researcher.gitcd ai-company-researcher# Install dependenciespip install -r requirements.txt# Install Playwright browsersplaywright install chromium# Set environment variables (optional)export GROQ_API_KEY="your_groq_api_key_here"# Run locallypython main.py
🎮 Usage
Using Apify Console
- Navigate to the Actor in your Apify Console
- Fill in the input form:
- Target Name: Enter company/product name or research topic
- Research Mode: Select "Company Analysis" or "General Topic Research"
- Groq API Key: (Optional) Enter your key for higher rate limits
- Click Start
- View results in the Dataset tab once complete
Using Apify API
// Node.js Exampleconst ApifyClient = require('apify-client');const client = new ApifyClient({token: 'YOUR_APIFY_TOKEN',});const run = await client.actor('your-actor-id').call({company_name: 'Stripe',mode: 'Company Analysis'});const { items } = await client.dataset(run.defaultDatasetId).listItems();console.log(items);
# Python Examplefrom apify_client import ApifyClientclient = ApifyClient('YOUR_APIFY_TOKEN')run = client.actor('your-actor-id').call(run_input={'company_name': 'Stripe','mode': 'Company Analysis'})dataset = client.dataset(run['defaultDatasetId']).list_items().itemsprint(dataset)
Local Execution
import asynciofrom main import EnhancedCompanyResearchScraperasync def main():scraper = EnhancedCompanyResearchScraper(company_name="Notion",groq_api_key="your_key_here" # Optional)results = await scraper.run_complete_research()# Save outputsscraper.save_to_json(results, "notion_research.json")scraper.save_analysis_text(results, "notion_analysis.txt")asyncio.run(main())
📝 Input Schema
Required Fields
| Field | Type | Description | Example |
|---|---|---|---|
company_name | string | Name of company, product, or topic | "Stripe", "React Framework" |
mode | select | Research type | "Company Analysis" or "General Topic Research" |
Optional Fields
| Field | Type | Description | Default |
|---|---|---|---|
groq_api_key | string | Your Groq API key | Uses fallback key |
Input Examples
Company Analysis:
{"company_name": "Figma","mode": "Company Analysis"}
Topic Research:
{"company_name": "Graph RAG","mode": "General Topic Research"}
📤 Output Schema
Output Structure
{"metadata": {"research_date": "2024-12-06T10:30:00Z","company_name": "Stripe","scraper_version": "2.0","analysis_model": "llama-3.3-70b-versatile"},"raw_data": {"website_data": { "homepage": {}, "pricing": {} },"pricing_tiers": [{"name": "Starter","price": "$29","billing_period": "month"}],"features": [{"name": "Payment Processing","description": "Accept payments worldwide"}],"news_articles": [],"reviews": [],"social_mentions": [],"competitors": []},"ai_deep_analysis": {"company_overview": {"description": "Stripe is a financial infrastructure platform...","industry": "Financial Technology","target_market": "Online businesses and platforms","value_proposition": "Easy-to-integrate payment processing","business_model": "Transaction fees and subscriptions"},"product_analysis": {},"pricing_strategy": {},"market_position": {},"competitive_landscape": {},"customer_sentiment": {},"strengths_weaknesses": {"top_5_strengths": ["Best-in-class API", "Strong brand", "..."],"top_5_weaknesses": ["Premium pricing", "Complex setup", "..."],"opportunities": ["B2B expansion", "Crypto integration"],"threats": ["Regulatory changes", "Increased competition"]},"strategic_insights": {},"actionable_recommendations": ["Consider Stripe for global payment processing","Evaluate pricing for low-volume businesses"],"executive_summary": "Stripe is a leading financial infrastructure...","risk_score": {"overall_score": "35","risk_factors": ["Regulatory compliance", "Account stability"],"confidence_level": "high"}},"metrics": {"pages_scraped": 8,"pricing_tiers_found": 4,"features_identified": 15,"news_articles": 10,"reviews_collected": 8,"competitors_identified": 12}}
🔬 Research Modes
1. Company Analysis Mode
Best For:
- Competitive intelligence
- Investment research
- Partnership evaluation
- Product comparison
Data Collected:
- Website content, pricing, features
- News and announcements
- Customer reviews and ratings
- Social media presence
- Competitor landscape
AI Analysis:
- Business model breakdown
- Market positioning
- SWOT analysis
- Customer sentiment
- Risk assessment
2. General Topic Research Mode
Best For:
- Technology trends
- Academic research
- Learning new concepts
- Industry analysis
Data Collected:
- Authoritative sources
- Latest developments
- Community discussions
- Implementation examples
AI Analysis:
- Technical deep dive
- State-of-the-art trends
- Pros and cons
- Future outlook
- Learning pathway
🛠️ Technical Stack
| Component | Technology | Purpose |
|---|---|---|
| Runtime | Python 3.11+ | Core execution environment |
| Web Scraping | Playwright | Headless browser automation |
| AI Analysis | Groq API | Llama 3.3 70B inference |
| Actor Framework | Apify SDK | Scalable execution & storage |
| Parsing | BeautifulSoup4, regex | Content extraction |
Dependencies
apify>=1.0.0playwright>=1.40.0groq>=0.4.0requests>=2.31.0rich>=13.0.0
📊 Examples
Example 1: Analyze a SaaS Company
{"company_name": "Notion","mode": "Company Analysis"}
Output Highlights:
- 10 pages scraped
- 3 pricing tiers identified
- 25+ features extracted
- 15 news articles collected
- Risk Score: 25/100 (Low Risk)
- Market Position: Strong growth trajectory
Example 2: Research a Technical Topic
{"company_name": "Retrieval Augmented Generation","mode": "General Topic Research"}
Output Highlights:
- 3 authoritative sources analyzed
- Technical architecture explained
- Current trends identified
- 5 use cases documented
- Future outlook: High disruption potential
🐛 Troubleshooting
Common Issues
| Issue | Solution |
|---|---|
| "Company website not found" | Verify company name is correct; use full name |
| "AI analysis failed" | Check Groq API key validity; may be rate limited |
| "No pricing found" | Pricing may be on request; check raw_data |
| Empty competitor list | Company may be too niche |
| Slow execution | Normal; typically takes 2-5 minutes |
Performance
- Total Runtime: 2-5 minutes
- Pages Scraped: 5-10 per company
- Output Size: 50-200 KB JSON
- Memory Usage: 500MB - 1GB
💡 Best Practices
- Use Specific Names: "Stripe Payment Processing" > "Payment Company"
- Check Domain Accuracy: Ensure the company has a website
- Use Custom API Key: For higher rate limits
- Review Outputs: AI analysis should be verified for critical decisions
📸 Visual Overview
📜 License
This project is licensed under the MIT License.
🎖️ Built For Apify Hackathon 2025
This Actor was developed as part of the Apify Hackathon 2024, showcasing the power of combining web scraping with advanced AI analysis for market intelligence.


