Dealroom Scraper | Companies and Investors (2026)

From SilentFlow. Creators of Facebook Search Scraper and Pinterest Scraper, with 540,000+ combined lifetime runs.

Turn any Dealroom company or investor into one clean row: every funding round, valuation, revenue, team, investors, portfolio, traffic and news. Three profiles in under 15 seconds, from a link, a website or just a name.

Why choose this actor?

Still opening Dealroom profiles one by one and copying numbers into a spreadsheet? Got a list of company websites or fund names but no Dealroom links? Tired of exports that stop at the headline totals and skip the round-by-round history?

• The whole profile, not the headline. A company row comes back with 71 to 88 filled fields: Stripe returns 81, with 22 funding rounds, 95 investors, 6 years of KPIs, 143 months of web traffic and 62 months of headcount. Investor rows are just as complete: Sequoia returns 50 fields, with 260 notable investments, 166 exits and 120 LP investors. On the prefilled run, 74 fields are filled on at least two rows out of three.
• Start from what you already have. Paste Dealroom links, website domains (stripe.com), website URLs (https://www.figma.com/) or plain names (Mistral AI, Index Ventures). Index Ventures, Revolut and Doctolib were found by name and returned in full in under 20 seconds, without a single link.
• Nothing to configure. No required field and no Dealroom account: the prefilled form runs as is and returns Stripe, Sequoia and Mistral AI in under 15 seconds. A figure Dealroom does not publish comes back empty (null), not as a blank text or a 0.

Try your first profile

Paste this input in the Input tab (or keep the prefilled form) and press Start:

{
  "startUrls": [
    { "url": "https://app.dealroom.co/companies/stripe" },
    { "url": "https://app.dealroom.co/investors/sequoia_capital" }
  ],
  "keywords": ["Mistral AI"],
  "maxItems": 10
}

You get three rows: Stripe (a company), Sequoia (an investor) and Mistral AI (found by name). Each row is a full profile you can open as a table, export to CSV or Excel, or read from the API.

This runs on the Apify Free plan: create an account, open the actor, press Start. No credit card is needed to try it.

SilentFlow · Dealroom suite
Dealroom Scraper You are here	Dealroom Startup Data Scraper Dealroom Startup Data

Copy to your AI assistant

Paste this block into Claude, ChatGPT or Cursor to give it full context about this actor:

You have access to the Dealroom Scraper on Apify: silentflow/dealroom-scraper-ppe
It returns one row per Dealroom company or investor profile.

Input (all optional, at least one of startUrls, domains or keywords):
- startUrls (array of {"url": string}): Dealroom profile URLs
  (https://app.dealroom.co/companies/<slug>, https://app.dealroom.co/investors/<slug>)
  or company website URLs (https://www.figma.com/)
- domains (array of strings): company website domains, e.g. stripe.com, doctolib.fr
- keywords (array of strings): company or investor names, e.g. "Mistral AI", "Index Ventures".
  Name search covers investors and well-known companies; use a domain or a Dealroom URL for the rest.
- maxItems (integer, default 50): maximum number of profiles saved
- includeTeam (boolean, default true): founders and key people
- includeFunding (boolean, default true): funding rounds and investor list
- includeNews (boolean, default true): recent news articles
- debugMode (boolean, default false)

Output per profile (115 fields, null when Dealroom does not publish the value):
- Identity: id, url, uuid, name, tagline, about, path, entityType, dealroomUrl, websiteUrl, logoUrl, logoSmall
- Status: companyStatus, growthStage, entitySubTypes, deliveryMethod, industries, subIndustries, tags, clientFocus, incomeStreams
- Location: hqCity, hqCountry, hqAddress, hqZip, locations[]
- Links: linkedinUrl, twitterUrl, facebookUrl, instagramHandle, careerPageUrl, appStoreAppId, playMarketAppId
- Team: teamTotal, founders[], keyPeople[], employeesLatest, employeeGrowthPercentile, employeeGrowthAbsolute, jobOffersTotal, employeesChart[]
- Funding: totalFunding, totalFundingCurrency, fundingRounds[] (type, amount, currency, year, month, valuation, investors), lastRoundType, lastRoundAmount, lastRoundDate (YYYY-MM), investorNames[], investors[], ownerships[]
- Valuation and financials: latestValuation, latestValuationCurrency, latestValuationMin, latestValuationMax, latestValuationYear, latestValuationMonth, latestValuationSource, marketCap, netDebt, revenue, revenueCurrency, revenueYear, kpiHistory[] (yearly revenue, growth, EBITDA, margins, valuation multiples), shareTickerSymbol, sharePrice, sharePriceChart[]
- Traffic: similarwebMonthlyVisits, trafficGrowthPercentile, trafficGrowthAbsolute, trafficSources[], trafficTopCountries[], similarwebChart[]
- Investor activity: investmentsCount, investments[], exitsCount, investorTotal, investorTotalRank, exitsFunding, recentFundingsCount, countryExperience[], industryExperience[], roundsExperience[], topInvestments[], topExits[], lpInvestments[], lpInvestors[], affiliatedFunds[]
- Other: legalEntities[], techStack[], recentNews[], dealroomLists[], patentsCount, innovationsCount, launchYear, launchMonth, closingYear, closingMonth, dealroomRank, dealroomScore, rankingsDetails
- Meta: inputUrl, scrapedAt (RFC 3339), dataType

Use apify-client (Python or JavaScript): client.actor("silentflow/dealroom-scraper-ppe").call(run_input=...)

How to scrape Dealroom company data

Get the full profile of a company you already know

{
  "startUrls": [{ "url": "https://app.dealroom.co/companies/klarna" }]
}

One row with Klarna's 36 funding rounds, valuation, revenue history, founders, investors, traffic and tech stack.

Turn a list of company websites into Dealroom profiles

{
  "domains": ["figma.com", "canva.com", "notion.so"],
  "maxItems": 10
}

Each website is matched to its Dealroom profile. The three above came back as Figma, Canva and Notion in about 10 seconds. A website that does not match the profile found is skipped rather than returned as the wrong company.

Research investors by name before a fundraise

{
  "keywords": ["Index Ventures", "Sequoia Capital"],
  "includeTeam": true,
  "includeNews": true,
  "maxItems": 10
}

Each investor row carries its notable investments, exits, LP relationships, the countries, sectors and rounds it invests in most, its partners and its recent news.

Input parameters

Parameter	Type	Default	What it does
startUrls	array	prefilled with Stripe and Sequoia	Dealroom profile URLs or company website URLs. One profile per line.
domains	array	empty	Company website domains such as stripe.com. One profile per domain.
keywords	array	prefilled with Mistral AI	Company or investor names. Each name returns its best matching profile.
maxItems	integer	50	Maximum number of profiles saved. The run stops when this many rows are in the dataset.
includeTeam	boolean	true	Adds founders and key people with their roles, LinkedIn links, education and past roles.
includeFunding	boolean	true	Adds every funding round and the full investor list. Totals and the last round stay in the row when it is off.
includeNews	boolean	true	Adds the latest news articles about the profile.
debugMode	boolean	false	Shows detailed logs of each step.

Accepted formats in startUrls:

• Dealroom company URL: https://app.dealroom.co/companies/stripe
• Dealroom investor URL: https://app.dealroom.co/investors/sequoia_capital
• Website URL: https://www.stripe.com/
• In domains, a bare domain: stripe.com

About keywords: name search covers investors and well-known companies (unicorns, high-growth and widely tracked companies). For a smaller company, give its Dealroom URL, which reaches every company Dealroom lists, or its website domain, which works when the company's Dealroom name or link matches the domain. A name with no match returns no row, and the run says so at the end.

Inputs from earlier versions keep working unchanged, including integrations and saved tasks that send fields no longer shown in the form.

What data can you extract from Dealroom?

Every profile row has the same 115 columns, so a CSV or a spreadsheet keeps its shape whatever the mix of companies and investors. A top-level value Dealroom does not publish is null.

Group	Fields	What you get
Identity	14	id, url, name, tagline, description, type, website, logo
Status and classification	15	operating status, growth stage, industries and sub-industries, tags, business model, client focus
Location and links	12	HQ city, country, address, every office, LinkedIn, X, Facebook, Instagram, careers page, app store links
Team	8	team size, founders, key people, headcount band, headcount growth, open jobs, monthly headcount history
Funding and investors	9	total funding, every round (type, amount, currency, date, valuation, investors), last round, investor list, ownership mix
Valuation and financials	19	latest valuation with its range and date, market cap, net debt, revenue, yearly KPIs, share price
Traffic and rankings	9	monthly web visits, traffic growth, traffic sources, top countries, monthly traffic history, Dealroom rank
Investor activity	16	investments, exits, notable investments and exits, LP relationships, country, sector and round experience
Other	10	legal entities, tech stack, recent news, Dealroom lists, patents, launch and closing dates
Meta	3	inputUrl, scrapedAt, dataType

Nested objects are rich on their own: a founder carries 21 fields (role, LinkedIn, education, work history, founder scores), a funding round 8, a news item 10 and a KPI year 12 (revenue, growth, EBITDA, margins, valuation multiples).

What one real run returned, measured on 21 October 2026:

Profile	Filled fields	Highlights
Stripe	81	22 funding rounds, 95 investors, 6 KPI years, 322 technologies
Klarna	88	36 funding rounds, 85 investors, 16 KPI years
Figma	83	11 funding rounds, 60 investors, 128 months of traffic
Mistral AI	71	10 funding rounds, 63 investors, 3 founders
Sequoia	50	260 notable investments, 166 exits, 120 LP investors
Index Ventures	50	82 notable investments, 46 exits, 59 LP investors

Data facts worth knowing:

• id is Dealroom's stable identifier and url the permanent profile link: both are safe keys to join runs over time.
• Amounts are plain numbers with their currency in a separate field (totalFunding and totalFundingCurrency).
• lastRoundDate is a month (2026-02): Dealroom records rounds by month. scrapedAt is a full RFC 3339 timestamp.
• Every run reads the profiles live, so a new round or a new valuation shows up as soon as Dealroom publishes it.

Output example

A real Stripe row from 21 October 2026, with each list cut to its first entry to keep the page short:

{
  "id": "90f1c9d8-2afe-4db3-b852-c01f6c904628",
  "url": "https://app.dealroom.co/companies/stripe",
  "uuid": "90f1c9d8-2afe-4db3-b852-c01f6c904628",
  "name": "Stripe",
  "tagline": "Integrated payments and finance automation with global reach",
  "about": "Stripe is a financial technology company that provides online payment processing solutions for internet businesses. I...",
  "path": "stripe",
  "entityType": "corporate",
  "inputUrl": "https://app.dealroom.co/companies/stripe",
  "dealroomUrl": "https://app.dealroom.co/companies/stripe",
  "websiteUrl": "http://stripe.com",
  "logoUrl": "https://storage.googleapis.com/dealroom-images-production/39/MTAwOjEwMDpjb21wYW55QHMzLWV1LXdlc3QtMS5hbWF6b25hd3MuY29t...",
  "logoSmall": null,
  "aboutAiGenerated": true,
  "isEditorial": false,
  "companyStatus": "operational",
  "growthStage": "late stage",
  "entitySubTypes": null,
  "deliveryMethod": "online",
  "corporateIndustries": null,
  "serviceIndustries": null,
  "isGovernment": false,
  "isNonProfit": false,
  "hqCity": "South San Francisco",
  "hqCountry": "United States",
  "hqAddress": "354, Oyster Point Boulevard, South San Francisco, San Mateo County, California, 94080, United States",
  "hqZip": "94080",
  "locations": [
    {
      "address": "542 Singel, 1017 AZ Amsterdam, North Holland, Netherlands",
      "city": "Amsterdam",
      "continent": "Europe",
      "country": "Netherlands",
      "isFoundingLocation": false,
      "isHq": false,
      "lat": 52.366645,
      "lon": 4.892397,
      "state": "North Holland",
      "street": "Singel",
      "streetNumber": "542",
      "zip": "1017 AZ"
    }
  ],
  "linkedinUrl": "https://www.linkedin.com/company/stripe/",
  "twitterUrl": "https://twitter.com/stripe",
  "facebookUrl": "https://www.facebook.com/stripehq",
  "instagramHandle": "stripehq",
  "careerPageUrl": "https://stripe.com/jobs",
  "industries": [
    "fintech"
  ],
  "subIndustries": [
    "payments"
  ],
  "tags": [
    "developer tools"
  ],
  "technologies": null,
  "teamTotal": 1664,
  "founders": [
    {
      "angellistUrl": null,
      "education": [
        {
          "degree": null,
          "majors": null,
          "universityName": "Massachusetts Institute of Technology",
          "universityPath": "massachusetts_institute_of_technology",
          "yearEnd": 2010,
          "yearStart": 2006
        }
      ],
      "founderScore": 127,
      "gender": "male",
      "imageUrl": "https://storage.googleapis.com/dealroom-images-production/e6/MTAwOjEwMDp1c2VyQHMzLWV1LXdlc3QtMS5hbWF6b25hd3MuY29tL2Rl...",
      "isExecutive": true,
      "isFounder": true,
      "isPartner": false,
      "isStrongFounder": false,
      "isSuperFounder": true,
      "linkedinUrl": "https://www.linkedin.com/in/patrickcollison/",
      "monthEnd": 0,
      "monthStart": 2,
      "name": "Patrick Collison",
      "path": "patrick_collison",
      "title": "Chief Executive Officer",
      "twitterUrl": null,
      "uuid": "e853bc21-a9b7-4f6b-a343-9bb1d46a8b22",
      "workHistory": [
        {
          "companyName": "Stripe",
          "companyPath": "stripe",
          "industries": [
            "fintech"
          ],
          "isPast": false,
          "title": "Chief Executive Officer",
          "totalFunding": 7941.02
        }
      ],
      "yearEnd": 0,
      "yearStart": 2009
    }
  ],
  "keyPeople": [
    {
      "angellistUrl": null,
      "education": [
        {
          "degree": null,
          "majors": null,
          "universityName": "Massachusetts Institute of Technology",
          "universityPath": "massachusetts_institute_of_technology",
          "yearEnd": 2010,
          "yearStart": 2006
        }
      ],
      "founderScore": 127,
      "gender": "male",
      "imageUrl": "https://storage.googleapis.com/dealroom-images-production/e6/MTAwOjEwMDp1c2VyQHMzLWV1LXdlc3QtMS5hbWF6b25hd3MuY29tL2Rl...",
      "isExecutive": true,
      "isFounder": true,
      "isPartner": false,
      "isStrongFounder": false,
      "isSuperFounder": true,
      "linkedinUrl": "https://www.linkedin.com/in/patrickcollison/",
      "monthEnd": 0,
      "monthStart": 2,
      "name": "Patrick Collison",
      "path": "patrick_collison",
      "title": "Chief Executive Officer",
      "twitterUrl": null,
      "uuid": "e853bc21-a9b7-4f6b-a343-9bb1d46a8b22",
      "workHistory": [
        {
          "companyName": "Stripe",
          "companyPath": "stripe",
          "industries": [
            "fintech"
          ],
          "isPast": false,
          "title": "Chief Executive Officer",
          "totalFunding": 7941.02
        }
      ],
      "yearEnd": 0,
      "yearStart": 2009
    }
  ],
  "employeesLatest": "10001+",
  "employeeGrowthPercentile": "top 25%",
  "employeeGrowthAbsolute": 54920,
  "jobOffersTotal": null,
  "totalFunding": 8735124999,
  "totalFundingCurrency": "USD",
  "fundingRounds": [
    {
      "amount": 0,
      "currency": "USD",
      "investors": null,
      "month": 2,
      "transactionMultiples": {
        "evEbitdaMultiple": 0,
        "evLtmEbitdaMultiple": 0,
        "evLtmProfitMultiple": 0,
        "evLtmRevenueMultiple": 0,
        "evNtmEbitdaMultiple": 0,
        "evNtmProfitMultiple": 0,
        "evNtmRevenueMultiple": 0,
        "evProfitMultiple": 0,
        "evRevenueMultiple": 27.22
      },
      "type": "SECONDARY",
      "valuation": 159000000000,
      "year": 2026
    }
  ],
  "lastRoundType": "SECONDARY",
  "lastRoundAmount": null,
  "lastRoundDate": "2026-02",
  "investorNames": [
    "American Express Ventures"
  ],
  "investors": [
    {
      "entityType": null,
      "isLead": false,
      "name": "American Express Ventures",
      "path": "american_express_ventures"
    }
  ],
  "investmentsCount": 80,
  "investments": [
    {
      "growthStage": null,
      "industries": null,
      "isExited": false,
      "name": "Monzo Bank",
      "path": "monzo_bank",
      "totalFunding": 0
    }
  ],
  "exitsCount": 5,
  "latestValuation": 159000000000,
  "latestValuationCurrency": "USD",
  "latestValuationMin": null,
  "latestValuationMax": null,
  "latestValuationYear": 2026,
  "latestValuationMonth": 2,
  "latestValuationSource": "funding",
  "marketCap": null,
  "marketCapCurrency": null,
  "netDebt": null,
  "netDebtCurrency": null,
  "revenue": 5840000000,
  "revenueCurrency": "USD",
  "revenueYear": 2025,
  "kpiHistory": [
    {
      "ebitda": 0,
      "ebitdaMargin": 0,
      "evEbitda": 0,
      "evRevenue": 22.5,
      "profit": 0,
      "profitMargin": 0,
      "revenue": 1600000000,
      "revenueGrowth": 0,
      "rnd": 0,
      "rndMargin": 0,
      "valuation": 36000000000,
      "year": 2020
    }
  ],
  "similarwebMonthlyVisits": 130000000,
  "trafficGrowthPercentile": null,
  "trafficGrowthAbsolute": 292941,
  "trafficSources": [
    {
      "type": "Search",
      "value": 15
    }
  ],
  "trafficTopCountries": [
    {
      "name": "United States",
      "value": 51
    }
  ],
  "dealroomRank": null,
  "dealroomScore": null,
  "rankingsDetails": null,
  "shareTickerSymbol": null,
  "sharePrice": null,
  "sharePriceCurrency": null,
  "patentsCount": null,
  "innovationsCount": null,
  "closingYear": null,
  "closingMonth": null,
  "investorTotal": 819,
  "investorTotalRank": "top 10%",
  "exitsFunding": null,
  "exitsFundingCurrency": null,
  "recentFundingsCount": 21,
  "countryExperience": [
    {
      "count": 60,
      "name": "United States"
    }
  ],
  "industryExperience": [
    {
      "count": 35,
      "name": "Fintech"
    }
  ],
  "roundsExperience": [
    {
      "count": 27,
      "name": "SEED"
    }
  ],
  "appStoreAppId": "https://apps.apple.com/app/id978516833",
  "playMarketAppId": "https://play.google.com/store/apps/details?id=com.stripe.android.dashboard",
  "legalEntities": [
    {
      "country": "United Kingdom",
      "isPrimary": true,
      "registeredName": "Stripe Developments Ltd",
      "registryName": "Companies House",
      "tradeRegisterNumber": "13369617",
      "tradeRegisterUrl": "https://find-and-update.company-information.service.gov.uk/company/13369617"
    }
  ],
  "techStack": [
    {
      "category": "operating systems & computing languages",
      "name": ".net"
    }
  ],
  "recentNews": [
    {
      "author": null,
      "categories": null,
      "imageUrl": "https://procoinnews.com/wp-content/uploads/2026/10/stablecoin-payments-482-billion.jpg",
      "link": "https://procoinnews.com/stablecoin-payments-482-billion-supply-barely-moves",
      "pubDate": "2026-10-18T20:19:16+00:00",
      "relatedCompanies": [
        {
          "entityType": "organization",
          "name": "Stripe",
          "path": "stripe"
        }
      ],
      "source": "PredictLeads",
      "sourceUrl": "https://predictleads.com",
      "summary": "Stablecoin payments hit $482 billion while supply barely moves.\n\nBy Isaac - October 18, 2026 3:19 pm -\n\nThe stablecoi...",
      "title": "Stablecoin payments hit $482 billion while supply barely moves."
    }
  ],
  "employeesChart": [
    {
      "date": "2021-10-01",
      "value": 1
    }
  ],
  "similarwebChart": [
    {
      "date": "2014-10-01",
      "value": 6100000
    }
  ],
  "topInvestments": [
    {
      "entityType": "organization",
      "growthStage": null,
      "name": "Monzo Bank",
      "path": "monzo_bank"
    }
  ],
  "topExits": null,
  "lpInvestments": [
    {
      "entityType": "organization",
      "growthStage": null,
      "name": "Common Magic",
      "path": "common_magic"
    }
  ],
  "lpInvestors": null,
  "affiliatedFunds": null,
  "ownerships": [
    {
      "entityType": null,
      "name": "Private Equity",
      "path": null
    }
  ],
  "dealroomLists": [
    {
      "id": 10586,
      "title": "Foreign tech companies in Amsterdam"
    }
  ],
  "sharePriceChart": null,
  "clientFocus": [
    "business"
  ],
  "incomeStreams": [
    "subscription"
  ],
  "sdgs": null,
  "launchYear": 2009,
  "launchMonth": 2,
  "scrapedAt": "2026-10-21T00:34:57Z",
  "dataType": "company"
}

Advanced usage

Enrich a CRM export with funding and headcount

{
  "domains": ["doctolib.fr", "revolut.com", "klarna.com"],
  "includeTeam": false,
  "includeNews": false,
  "maxItems": 500
}

Turn off team and news when you only need the firmographics: rows come back faster and still carry funding, valuation, revenue, headcount and traffic. Export the dataset as CSV and join it back on the domain.

Map a fund's portfolio and co-investors

{
  "keywords": ["Index Ventures"],
  "includeFunding": true
}

topInvestments, topExits, lpInvestors and the three experience lists (countryExperience, industryExperience, roundsExperience) describe where and how the fund invests. Feed the path of each notable investment back into startUrls as https://app.dealroom.co/companies/<path> to pull the full company rows.

Track a watch list every week

{
  "startUrls": [
    { "url": "https://app.dealroom.co/companies/mistral_ai" },
    { "url": "https://app.dealroom.co/companies/figma" }
  ],
  "includeNews": true
}

Save this input as a task and schedule it weekly in Apify. Compare lastRoundType, lastRoundDate, latestValuation and employeesLatest between runs on id to spot new rounds, valuation changes and hiring.

Mix links, domains and names in one run

{
  "startUrls": [{ "url": "https://app.dealroom.co/companies/stripe" }],
  "domains": ["canva.com"],
  "keywords": ["Index Ventures", "Doctolib"],
  "maxItems": 20
}

All inputs are read in parallel and land in one dataset. The same profile reached twice (a link and a name) is saved once.

Pull the rows into Python for analysis

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("silentflow/dealroom-scraper-ppe").call(run_input={
    "keywords": ["Mistral AI", "Revolut", "Doctolib"],
    "includeNews": False,
})
rows = list(client.dataset(run["defaultDatasetId"]).iterate_items())
for r in sorted(rows, key=lambda r: r.get("totalFunding") or 0, reverse=True):
    print(r["name"], r.get("growthStage"), r.get("totalFunding"), r.get("lastRoundType"), r.get("lastRoundDate"))

Rows sort by total funding, with the last round next to each. The same dataset is available as CSV, Excel, JSON or XML from the Storage tab or from https://api.apify.com/v2/datasets/<datasetId>/items?format=csv.

FAQ

What is Dealroom? Dealroom is a database of startups, scale-ups and investors used by venture funds, corporates and governments to track funding, valuations and growth. It is comparable to Crunchbase, with especially deep coverage of European companies and funds.

Do I need a Dealroom account or API key? No. The actor reads the public profile pages. You do not need a Dealroom subscription, a login or an API key.

What exactly does one row contain? One Dealroom profile with 115 columns: identity, status, location, team, funding rounds, investors, valuation, revenue and KPIs, traffic, investor activity, tech stack and news. Companies fill 71 to 88 of them on the profiles above, investors around 50.

Can I search by company name? Yes, with keywords. Name search covers investors and well-known companies. For a smaller company, paste its Dealroom URL (every listed company has one) or its website domain (found when its Dealroom name or link matches the domain).

Why are some fields empty? Dealroom does not publish every figure for every company: revenue and valuation are often missing for young startups, and an investor has no funding rounds of its own. A missing top-level value is null, not a blank text or a 0. Inside lists (funding rounds, traffic shares, portfolio entries) numbers stay as Dealroom gives them, so an undisclosed round amount reads 0.

How fresh is the data? Live. Every run reads the profiles at the time of the run, so the rows match what Dealroom shows that day.

How many profiles can I scrape in one run? As many as you list. maxItems caps the number of rows saved (50 by default); raise it for long lists. Profiles are read several at a time.

Can I scrape several companies and investors in the same run? Yes. Mix Dealroom links, domains and names freely; every profile becomes its own row in the same dataset, and a profile reached twice is saved once.

What happens when a website does not match a Dealroom profile? The input is skipped instead of returning a different company. The log names every input that found nothing, and a run that saves no row ends with a message saying why.

Will my existing integrations or saved tasks break? No. Every input and every output field name from earlier versions is kept, and id, url and keywords were added next to them. One change to plan for: a value Dealroom does not publish is now null instead of an empty text or a 0.

Can I export to Excel or Google Sheets? Yes. Download the dataset as CSV, Excel or JSON from the run, or connect Google Sheets, Zapier, Make or any tool through the Apify integrations.

More SilentFlow scrapers

🛒 E-commerce

• Pinterest - Pinterest Scraper | Pins, Boards and Profiles
• Leboncoin - Leboncoin Scraper | Classified Ads, Prices and Sellers
• JD - JD Products Scraper | JD.com Prices, Brands and Barcodes
• Leboncoin - Leboncoin Ad Details Scraper
• TikTok Shop - TikTok Shop Scraper | Products, Sellers and Creator Videos
• Back Market - Back Market Scraper | Refurbished Prices
• ImportYeti - US Customs Records, Suppliers & Trade Data - ImportYeti Scraper - US Customs Records, Suppliers & Trade Data
• Naver - Naver Scraper | Shopping Products, Prices and Reviews
• Udemy Course - Udemy Course Scraper
• Naver - Naver Products Scraper | Shopping Prices, Sellers and Ratings
• 1688 - 1688 Scraper | Products, Details, Wholesale Prices, Suppliers
• Naver - Naver Reviews Scraper | Shopping Product Reviews
• Amazon Seller - Amazon Seller Scraper | Emails, Phones and Ratings
• Store Leads Ecommerce - Store Leads Ecommerce Scraper
• Store Leads - Store Leads Scraper | Shopify Data
• Allegro - Allegro Scraper | Products, Prices and Sellers
• Leboncoin - Leboncoin Scraper
• Bring a Trailer - Bring a Trailer Scraper
• Lowes - Lowes Products Scraper | Prices, Stock and Specs
• Mobile.de - Mobile.de Scraper
• Taobao - Taobao Scraper | Products, Details, Prices and Sellers
• Agoda - Agoda Scraper | Hotel Prices and Guest Ratings
• Alibaba - Alibaba Products Scraper | Wholesale Prices and MOQ
• Avito - Avito Scraper | Listings, Prices and Sellers
• Udemy - Udemy Scraper
• Alibaba - Alibaba Scraper | Products, Supplier Companies and Prices
• AliExpress - AliExpress Reviews Scraper | Feedback, Ratings and Photos
• AliExpress - AliExpress Scraper | Products, Prices and Sales
• Avito - Avito Profiles Scraper | Sellers, Ratings and Reviews
• Back Market - Back Market Scraper | Refurbished Electronics Prices
• BAUHAUS - BAUHAUS Scraper | Product Prices, EAN and Specs
• CARFAX - CARFAX Scraper | Used Cars, Prices and History
• Coupang - Coupang Detail Scraper | Product Prices and Options
• eBay Marketplace - eBay Marketplace Scraper
• Europages - Europages Scraper | Suppliers and B2B Companies
• Eventim - Eventim Scraper | Events, Ticket Prices and Venues
• Google Hotels - Google Hotels Scraper | Prices, Offers and Ratings
• Homedepot - Homedepot Reviews Scraper | Customer Reviews and Ratings
• Leboncoin - Leboncoin Details Scraper | Full Ad Data and Sellers
• Mafengwo - Mafengwo Scraper | Attractions, Ratings and Tickets
• Mercari - Mercari Scraper | Listings, Sold Prices and Sellers
• Pinterest - Pinterest Scraper
• Vinted Marketplace - Vinted Marketplace Scraper
• Webmotors - Webmotors Scraper | Car Listings, Prices and FIPE
• Amazon - Amazon Product Scraper
• Amazon Marketplace - Amazon Marketplace Scraper
• AutoScout24 - AutoScout24 Scraper
• eBay Listings - eBay Listings Scraper
• Europages Deep Dive Extractor - Europages Deep Dive Extractor | VAT, Decision Makers, ISO Certs
• GasBuddy - GasBuddy Scraper | Gas Prices by Station
• Goofish - Goofish Detail Scraper | Listings, Prices and Sellers
• Trip - Trip Scraper | Hotels, Prices and Reviews
• Vinted - Vinted Scraper
• Walmart - Walmart Scraper | Prices, Reviews, Sellers, Availability
• Walmart - Walmart Product Scraper

💼 Jobs

• ZipRecruiter - ZipRecruiter Jobs Scraper | Salary, Company & Location Filters
• Indeed - Indeed Company Reviews Scraper
• Multi Board - Multi Board Job Scraper
• Glassdoor Job Listings - Glassdoor Job Listings Scraper
• Malt - Malt Scraper | Freelance Profiles
• 🔥 Glassdoor - 🔥 Glassdoor Scraper
• Jora - Jora Jobs Scraper
• Malt Freelancer - Malt Freelancer Scraper
• ATS - ATS Jobs Scraper | Greenhouse, Lever and Ashby
• Glassdoor - Glassdoor Jobs Scraper
• Jobright - Jobright Scraper | Jobs, Salaries and H1B Sponsors
• LinkedIn Job Search - LinkedIn Job Search Scraper | Salaries & Seniority
• Arbeitsagentur - Arbeitsagentur Jobs Scraper
• Cutshort - Cutshort Jobs Scraper | Salaries, Skills and Companies
• Dice - Dice Jobs Scraper | US Tech Jobs, Salaries, Skills
• Dice Tech - Dice Tech Jobs Scraper
• iimjobs - iimjobs Jobs Scraper | MBA, Finance and Hirist Tech Jobs
• Indeed - Indeed Jobs Scraper | Job Listings in 73 Countries
• Instahyre - Instahyre Jobs Scraper | Companies, Recruiters and Ratings
• Jora - Jora Scraper | Jobs in Australia, New Zealand, Singapore
• StepStone - StepStone Scraper
• Welcome to the Jungle - Welcome to the Jungle Job Scraper
• YCombinator - YCombinator Jobs Scraper | Startup Jobs, Salaries and Founders
• All - All Jobs Scraper
• Arbeitsagentur - Arbeitsagentur Scraper | German and Austrian Job Board
• iimjobs - iimjobs Scraper | Jobs, Companies and Recruiters
• Indeed - Indeed Companies Scraper | Reviews, Salaries, Interviews
• Indeed - Indeed Jobs Scraper | NLP Skills
• LinkedIn - LinkedIn Jobs Scraper
• Naukri & NaukriGulf - Naukri & NaukriGulf Jobs Scraper
• Seek - Seek Job Scraper
• Welcome to the Jungle - Welcome to the Jungle Scraper | Jobs and Company Data
• Ziprecruiter - Ziprecruiter Scraper

🏠 Real estate

• SeLoger - SeLoger Scraper | Real Estate Listings
• Realtor Rental Listings - Realtor Rental Listings Scraper
• Airbnb Pro Host Contact & - Airbnb Pro Host Contact & Email Scraper
• Airbnb Professional Host - Airbnb Professional Host Scraper | Emails, Phones, SIRET
• Trulia Rental Listings - Trulia Rental Listings Scraper
• Bien'ici - Bien'ici Scraper | Property Listings
• Rightmove - Rightmove Scraper
• Bienici - Bienici Scraper
• SeLoger - SeLoger Scraper | French Property Listings and Agencies
• Airbnb Search - Airbnb Search Scraper
• Idealista - Idealista Scraper
• Realestate.com.au - Realestate.com.au Scraper
• Airbnb Search - Airbnb Search Scraper | Prices, Fees, Amenities, Hosts
• Anjuke - Anjuke Scraper | Rental Listings, Prices and Agents
• Idealista - Idealista Scraper
• Realtor Rental - Realtor Rental Scraper
• Trulia Rental - Trulia Rental Scraper | US Rentals, Prices, Pet Policy
• Zillow - Zillow Scraper

📣 Social media

• LinkedIn Post Search - LinkedIn Post Search Scraper | Keywords, Hashtags & Profiles
• Facebook Search - Facebook Search Scraper
• Instagram - Instagram Story Scraper | Stories & Highlights
• LinkedIn Leads - LinkedIn Leads Scraper | Sales Navigator Export
• YouTube - YouTube Channel Scraper | Videos, Shorts and Views
• TikTok - TikTok Scraper
• Facebook Search - Facebook Search Profiles Scraper | People by Name or Keyword
• Instagram Engagement - Instagram Engagement Scraper
• OnlyFans - OnlyFans Profile Scraper
• TikTok Trend - TikTok Trend Scraper | Trending Hashtags and Videos
• Meta Ad Library - Meta Ad Library Scraper
• OnlyFans - OnlyFans Creator Scraper
• Skool Community - Skool Community Scraper
• Discord - Discord Scraper | Servers, Member Counts and Invites
• Douyin - Douyin Comments Scraper | Comments, Likes and IP Regions
• Facebook Thread - Facebook Thread Profiles Scraper | Followers, Bios & Engagement
• Kuaishou - Kuaishou Scraper | Videos, Comments and Creator Stats
• Likee - Likee Scraper | Videos, Hashtags and Creators
• LinkedIn Ads Library - No Cookies - LinkedIn Ads Library Scraper - No Cookies
• LinkedIn Event - LinkedIn Event Scraper
• LinkedIn Hashtag & - LinkedIn Hashtag & Post Scraper | No Cookies
• Pinterest - Pinterest Ads Scraper | Ad Library, Reach & Targeting
• Pinterest - Pinterest Profiles Scraper | Followers, Emails and Bios
• Pinterest - Pinterest Videos Scraper | Video Downloader, MP4 Links, Stats
• Reddit - Reddit Comments Scraper | Search, Threads and Replies
• Reddit - Reddit Profiles Scraper | User Karma, Activity and Communities
• Reddit - Reddit Scraper | Posts, Comments and Subreddits
• Reddit - Reddit Scraper | Comments, Posts and Users
• RedNote - RedNote Detail Scraper | Xiaohongshu Details, Images, Videos
• RedNote - RedNote Videos Scraper | Downloader, Transcripts and Stats
• Snapchat - Snapchat Contacts Scraper | Phones, Emails and Websites
• Snapchat - Snapchat Videos Scraper | Spotlight Videos, MP4 and Stats
• TikTok Creative - TikTok Creative Ads Scraper | Top Ads, Landing Pages & Metrics
• TikTok Lookalike - TikTok Lookalike Scraper | Influencers, Emails and Engagement
• Weibo - Weibo Scraper | Posts, Profiles and Engagement
• Xigua - Xigua Scraper | Videos, Creators and Downloads
• YouTube Autocomplete - YouTube Autocomplete Scraper | Keyword Suggestions
• Facebook - Facebook Company Scraper | Emails, Phones, Ratings
• Facebook Business Page - Facebook Business Page Scraper
• Kwai - Kwai Scraper | Videos, Creators and Hashtags
• Skool Group - Skool Group Scraper
• Snapchat - Snapchat Ads Scraper | Ad Library, Impressions & Targeting
• TwitchTracker - TwitchTracker Scraper | Twitch Streamer Stats and Rankings
• YouTube - YouTube Transcript Scraper

🏢 Business data

• Tencent - Tencent Scraper | Maps Places, Phones and Ratings
• LinkedIn Company Search - LinkedIn Company Search Scraper | Profiles & Firmographics
• LinkedIn People Search - LinkedIn People Search Scraper | Profiles & Companies
• ForexFactory - ForexFactory Scraper | Economic Calendar and Forecasts
• Justdial - Justdial Companies Scraper | Business Leads, Phones and Emails
• Kakao - Kakao Scraper | Map Places, Reviews and Phones
• Bilibili - Bilibili Scraper | Videos, Profiles, Comments, Danmaku
• Ctrip - Ctrip Scraper | Attractions, Tickets and Reviews
• FanDuel - FanDuel Scraper | Odds, Spreads and Player Props
• LinkedIn Sales Navigator - LinkedIn Sales Navigator Scraper
• OpenTable - OpenTable Reviews Scraper | Restaurant Reviews and Ratings
• SoftwareAdvice - SoftwareAdvice Scraper | Reviews, Ratings and Pros & Cons
• Teachable Course - Teachable Course Scraper
• Website Tech Stack - Website Tech Stack Scraper
• Zomato - Zomato Reviews Scraper | Restaurant Ratings and Replies
• 2GIS - 2GIS Reviews Scraper | Ratings, Photos and Owner Replies
• Teachable - Courses, Prices & Instructors - Teachable Scraper - Courses, Prices & Instructors
• Trustpilot - Trustpilot Scraper | Reviews, Ratings and Company Contacts

✈️ Travel

• Google Maps - Google Maps Scraper
• Flight Price - Flight Price Scraper
• Booking.com Hotel - Booking.com Hotel Scraper
• Trip - Trip Reviews Scraper | Hotel Reviews and Ratings
• Booking - Booking Scraper | Hotel Prices, Photos, Availability

🎯 Lead generation

• Northdata - Northdata Company Scraper
• ZocDoc - ZocDoc Scraper | Doctors, Reviews and Availability
• UK Companies House - UK Companies House Enricher
• CNPJ Brazilian - CNPJ Brazilian Company Enricher
• Google Ads Transparency - Google Ads Transparency Scraper
• BuiltWith - BuiltWith Scraper | Tech Stacks and Top Sites
• Company Data - Company Data Scraper | Emails, Phones and Tech Stack
• Domain - Domain Enricher
• French Company Prospector - French Company Prospector
• PagesJaunes - PagesJaunes Scraper | French Business Emails and SIRET
• SEC - SEC Scraper | EDGAR Filings and Company Data
• SIRET - SIRET Company Enricher
• USPTO - USPTO Scraper | Trademark Search and Status
• Clutch - Clutch Scraper | Agencies, Reviews, Ratings, Services
• Clutch Agency - Clutch Agency Scraper
• G2 - G2 Reviews Scraper
• PagesJaunes - PagesJaunes Business Scraper
• SIRET French - SIRET French Company Enricher
• ThomasNet Suppliers - ThomasNet Suppliers Scraper
• ZocDoc - ZocDoc Scraper

🔎 SEO

• Similarweb - Similarweb Scraper | Website Traffic, Rankings and Competitors
• Apple - Apple Reviews Scraper | App Store Reviews and Ratings
• Apple - Apple Scraper | App Store Apps, Ratings and Charts
• Google News - Google News Scraper

📈 Marketing

• Pexels - Pexels Scraper | Photos, Videos and Download Stats
• Douyin - Douyin Transcript Scraper | Subtitles and Speech to Text

🧰 More tools

• PrizePicks - PrizePicks Scraper | Player Props, Lines and Projections

Support

Need something this scraper doesn't do yet? We ship features fast.

• Feature requests go straight to our backlog
• Enterprise needs? We do custom integrations and high-volume plans
• Pricing questions? Check the Monetization tab on the actor page

Response time: usually under 24 hours.

Legal compliance

This Actor extracts publicly available data from Dealroom. It does not bypass any login, paywall or CAPTCHA. Users are responsible for complying with Dealroom's terms of service and applicable data protection laws (GDPR, CCPA, and PIPL where relevant). Rows can contain personal data about founders and team members (names, roles, public profile links): handle it according to those laws. The data returned is informational; verify accuracy before using it in regulated decisions.

Built by SilentFlow for teams that research startups and investors. Last tested on 21 October 2026.