DealRoom Scraper | Fast & Reliable | $8 / 1k

Slug: fatihtahta/dealroom-scraper Price: $8.00 per 1,000 saved records

High-speed, robust scraping of Dealroom lists and company profiles. Paste one or more Dealroom URLs and get a clean, deduplicated, analysis-ready dataset with rich company fields (funding, headcount trends, tags, social links, locations, etc.).

🧠 Typical Use Cases

• Market mapping: Export complete landscapes and segments (e.g., “AI startups”, “Fintech in Europe”) for analysis.
• Deal sourcing / BD: Pull structured profiles to discover targets faster.
• Competitive research: Track peers’ funding, growth, and team size changes.
• Enrichment: Join normalized Dealroom data to your internal company lists.

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📥 Input Configuration

This actor is intentionally simple. Provide Dealroom URLs and an optional max limit.

• startUrls (array, required) — One or more Dealroom app URLs. Supported types:

  • List URLs: https://app.dealroom.co/lists/{LIST_ID}/list/...

    • You can pass filter-encoded paths such as /list/f/landscapes/anyof_1834,999/industries/allof_42

  • Company URLs: https://app.dealroom.co/companies/{slug}

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🧪 Example Inputs

1) Scrape a filtered list (landscape filter shown):

{
  "startUrls": [
    "https://app.dealroom.co/lists/17482/list/f/landscapes/anyof_1834"
  ],
  "limit": 2000
}

2) Mix a list and a specific company profile:

{
  "startUrls": [
    "https://app.dealroom.co/lists/17482/list/f/industries/anyof_42",
    "https://app.dealroom.co/companies/openai"
  ],
  "limit": 1000
}

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📦 Output (Normalized Fields)

Each saved item represents a company record with a stable shape across both flows:

• Identifiers & basics: uuid, name, type, path
• Employees & charts: employees, employees_chart[]
• Taxonomy & tags: industries[], sub_industries[], tags[], entity_sub_types
• Founders & investors: founders[{ uuid, name }], investors[{ uuid, name, type }]
• Financials & KPIs: total_funding_enhanced, latest_valuation_enhanced, latest_revenue_enhanced, revenues[], kpi_summary
• Tech & products: technologies[], tech_stack[], innovations_count, images{...}
• Presence & links: links.website, links.linkedin, links.twitter, links.facebook, links.instagram, links.career_page
• Locations: hq_locations[{ country, city, lat, lon }]
• Lists & meta: lists[{ id, title }], date_added_to_list, _meta{ listId, entitySlug, sourceUrl, offset, ingestedAt }
• Select raw highlights: _raw_keep{ startup_ranking_rating, growth_stage, company_status }

Formats: Download as JSON, CSV, Excel, or HTML from the Dataset UI.

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💰 Pricing

$8.00 per 1,000 saved records. This actor uses Apify Pay-Per-Event and charges per saved dataset item using the event key outputrecord. If a record isn’t saved, you don’t pay for it.

Examples

• 2,500 records → (2,500 / 1,000) * $8.00 = $20.00
• 20,000 records → (20,000 / 1,000) * $8.00 = $160.00

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⚖️ Legal & Responsible Use

This actor aggregates publicly available business information from Dealroom’s app experience. Your output may include personal data (e.g., founder names). Ensure you have a lawful basis to process personal data and that your use complies with applicable laws (e.g., GDPR/CCPA) and the source’s terms.

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❓ Support

Questions, feature requests, or custom workflows? Open an issue on the actor’s Issues tab in Apify Console, and I’ll jump on it.

Happy Scraping, Fatih