Carnot Search

Overview

Carnot Search provides powerful company search capabilities to find detailed business information. With both standard and Pro versions, you can access comprehensive company databases for market research, lead generation, and business intelligence.

Key Features

CARNOT_SEARCH_CORP

Basic company search functionality
Find company information by name or criteria
Retrieve company URLs and addresses
Configurable result count

CARNOT_SEARCH_CORP_PRO

Enhanced search capabilities
More detailed company information
Advanced filtering options
Higher accuracy and coverage

Authentication

Carnot Search requires API keys from both Perplexity and OpenAI for enhanced search capabilities. Required credentials:

Perplexity API Key
OpenAI API Key

Note: Treat API keys as sensitive information and never commit them to public repositories.

Example: Basic Company Search

- id: search_companies
  name: search_companies
  tool: CARNOT_SEARCH_CORP
  config:
    - name: perplexity_api_key
      value: "{{secrets.PERPLEXITY_API_KEY}}"
    - name: openai_api_key
      value: "{{secrets.OPENAI_API_KEY}}"
  input:
    - name: query
      value: "software companies in San Francisco"
    - name: num_results
      value: 10

- id: process_search_results
  name: process_search_results
  tool: PYTHON_SANDBOX_RUN
  input:
    - name: code
      value: |
        import json
        
        # Process search results
        results = {{steps.search_companies.result.companies}}
        
        print("Company Search Results:")
        print("=" * 50)
        
        for i, company in enumerate(results, 1):
            print(f"{i}. {company.get('name', 'Unknown')}")
            print(f"   URL: {company.get('url', 'N/A')}")
            print(f"   Address: {company.get('address', 'N/A')}")
            print()
        
        print(f"Total companies found: {len(results)}")

Example: Enhanced Pro Search

- id: advanced_company_search
  name: advanced_company_search
  tool: CARNOT_SEARCH_CORP_PRO
  config:
    - name: perplexity_api_key
      value: "{{secrets.PERPLEXITY_API_KEY}}"
    - name: openai_api_key
      value: "{{secrets.OPENAI_API_KEY}}"
  input:
    - name: query
      value: "fintech startups with Series A funding in New York"
    - name: num_results
      value: 20

- id: analyze_competitive_landscape
  name: analyze_competitive_landscape
  tool: OPENAI_INVOKE
  config:
    - name: version
      value: gpt-4
  input:
    - name: prompt
      value: |
        Analyze the following company search results and provide insights:
        
        {{steps.advanced_company_search.result.companies | json}}
        
        Please provide:
        1. Market trends analysis
        2. Geographic distribution
        3. Company size patterns
        4. Key players identification
        5. Competitive landscape overview

- id: export_company_data
  name: export_company_data
  tool: CONVERTER_ARRAY_TO_CSV
  input:
    - name: array
      value: |
        [
          ["Company Name", "Website", "Address", "Search Score"],
          {% for company in steps.advanced_company_search.result.companies %}
          ["{{company.name}}", "{{company.url}}", "{{company.address}}", "High"]{% if not loop.last %},{% endif %}
          {% endfor %}
        ]

Example: Market Research Workflow

- id: search_competitors
  name: search_competitors
  tool: CARNOT_SEARCH_CORP_PRO
  config:
    - name: perplexity_api_key
      value: "{{secrets.PERPLEXITY_API_KEY}}"
    - name: openai_api_key
      value: "{{secrets.OPENAI_API_KEY}}"
  input:
    - name: query
      value: "{{input.industry}} companies in {{input.target_region}}"
    - name: num_results
      value: 50

- id: enrich_company_data
  name: enrich_company_data
  tool: PYTHON_SANDBOX_RUN
  input:
    - name: code
      value: |
        import json
        import re
        from urllib.parse import urlparse
        
        companies = {{steps.search_competitors.result.companies}}
        enriched_data = []
        
        for company in companies:
            # Extract domain from URL
            domain = ""
            if company.get('url'):
                try:
                    domain = urlparse(company['url']).netloc
                except:
                    domain = company['url']
            
            # Analyze company size based on address/description
            size_indicator = "Unknown"
            address = company.get('address', '').lower()
            if any(term in address for term in ['suite', 'floor', 'building']):
                size_indicator = "Medium-Large"
            elif any(term in address for term in ['street', 'ave', 'road']):
                size_indicator = "Small-Medium"
            
            enriched = {
                "name": company.get('name', ''),
                "url": company.get('url', ''),
                "domain": domain,
                "address": company.get('address', ''),
                "estimated_size": size_indicator
            }
            enriched_data.append(enriched)
        
        print(json.dumps(enriched_data, indent=2))

- id: create_market_report
  name: create_market_report
  tool: OPENAI_INVOKE
  config:
    - name: version
      value: gpt-4
  input:
    - name: prompt
      value: |
        Create a comprehensive market research report based on this company data:
        
        {{steps.enrich_company_data.result.stdout}}
        
        Include:
        1. Executive Summary
        2. Market Size Assessment
        3. Key Players Analysis
        4. Geographic Distribution
        5. Competitive Landscape
        6. Market Opportunities
        7. Recommendations
        
        Format as a professional business report.

- id: save_market_report
  name: save_market_report
  tool: OUTPUT_FILE
  input:
    - name: content
      value: "{{steps.create_market_report.result.content}}"
    - name: filename
      value: "market_research_report_{{date | format('YYYY-MM-DD')}}.txt"
    - name: fileType
      value: "txt"

Example: Lead Generation Pipeline

- id: find_potential_leads
  name: find_potential_leads
  tool: CARNOT_SEARCH_CORP
  config:
    - name: perplexity_api_key
      value: "{{secrets.PERPLEXITY_API_KEY}}"
    - name: openai_api_key
      value: "{{secrets.OPENAI_API_KEY}}"
  input:
    - name: query
      value: "{{input.target_industry}} companies with 10-100 employees"
    - name: num_results
      value: 25

- id: qualify_leads
  name: qualify_leads
  tool: OPENAI_INVOKE
  config:
    - name: version
      value: gpt-4
  input:
    - name: prompt
      value: |
        Analyze these potential leads and score them for sales qualification:
        
        {{steps.find_potential_leads.result.companies | json}}
        
        Scoring criteria:
        - Company size and growth potential (1-10)
        - Industry fit (1-10)
        - Geographic accessibility (1-10)
        - Technology alignment (1-10)
        
        Return a scored list with recommendations for follow-up.

- id: export_qualified_leads
  name: export_qualified_leads
  tool: CONVERTER_ARRAY_TO_CSV
  input:
    - name: array
      value: |
        [
          ["Company", "Website", "Address", "Qualification Score", "Priority", "Notes"],
          {% for company in steps.find_potential_leads.result.companies %}
          ["{{company.name}}", "{{company.url}}", "{{company.address}}", "TBD", "Medium", "Follow up required"]{% if not loop.last %},{% endif %}
          {% endfor %}
        ]

Search Parameters

Query Optimization

Use specific industry terms
Include geographic qualifiers
Specify company size when relevant
Use boolean operators for complex searches

Result Management

Start with smaller result sets (10-20)
Increase for comprehensive research (50+)
Consider API rate limits
Balance accuracy vs coverage

Use Cases

Market Research: Identify competitors and market players
Lead Generation: Find potential customers and partners
Investment Research: Analyze market sectors and opportunities
Competitive Intelligence: Monitor competitor landscape
Partnership Development: Discover potential business partners
Sales Prospecting: Build targeted prospect lists
Due Diligence: Research companies for business decisions

Data Structure

Search results include:

{
  "name": "Company Name",
  "url": "https://company-website.com",
  "address": "123 Business St, City, State, ZIP"
}

Best Practices

Query Design: Use specific, targeted search terms
Result Processing: Always validate and enrich search results
Rate Limiting: Respect API limits and implement delays
Data Quality: Clean and verify company information
Privacy: Handle company data responsibly and legally

​Overview

​Key Features

​CARNOT_SEARCH_CORP

​CARNOT_SEARCH_CORP_PRO

​Authentication

​Example: Basic Company Search

​Example: Enhanced Pro Search

​Example: Market Research Workflow

​Example: Lead Generation Pipeline

​Search Parameters

​Query Optimization

​Result Management

​Use Cases

​Data Structure

​Best Practices