VentureRadar Company Discovery API | Startup Database

Startup database profiles for emerging companies, as clean, structured JSON. Send company profile URLs and get back what the company does, its sector focus, founding year, location, social links, scoring, and the accelerators, incubators, and awards behind it.

The field that sets this apart is funding signals: not how much a company raised, but who backed it. Y Combinator, Techstars, a national innovation grant, a startup competition placing. That provenance is what deal-sourcing actually filters on, and it is rarely available as structured data.

What this actor returns

• Funding signals: accelerator, incubator, grant, and award provenance, each with a source link
• Milestones: dated company events such as accelerator batches and competition placements
• Company basics: name, description, website, founding year, ownership status, location
• Sector focus: areas of focus and descriptive keywords
• Scoring: analyst score, popularity, social proof, and website traffic sub-scores
• Social: LinkedIn and X profiles where listed

Every company row also carries a one-line plain-language summary, so an AI agent can read a record without post-processing.

Use cases

• Source deals by backer. Pull a set of companies and filter for the ones an accelerator or incubator has backed.
• Enrich a startup list. Attach sector focus, founding year, and location to companies you are already tracking.
• Track emerging companies in a sector. Areas of focus and keywords let you group companies by what they actually build.
• Screen inbound. Analyst and social-proof scores give a fast first-pass signal on an unfamiliar company.
• Build a competitive map. Similar-company links point at comparable businesses to collect next.

Input parameters

Parameter	Type	Required	Default	Description	Example
companyUrls	array of strings	Required	(none)	Company profile URLs. The company name and the profile id are both part of the URL and both are required. Up to 1000 per run.	["https://www.ventureradar.com/organisation/Theneo/b40ae154-6867-456f-a215-d98fdae0048c"]

{
  "companyUrls": [
    "https://www.ventureradar.com/organisation/Theneo/b40ae154-6867-456f-a215-d98fdae0048c"
  ]
}

There is no shorthand form. A company name on its own cannot be resolved to a profile, because the source keys profiles by name and id together.

Example output

One dataset row per input URL. Every row carries a result_type of either company or error, so a run is safe to process in a single pass.

Company rows can contain: companyId, companyName, profileUrl, website, description, descriptionSource, location, country, founded, ownership, keywords, areasOfFocus, linkedin, twitter, websitePopularity, analystScore, scores, fundingSignals, milestones, similarCompanies, summary, and fetched_at. Error rows carry sourceUrl, error_message, error_type, and fetched_at.

{
  "result_type": "company",
  "companyName": "Theneo",
  "website": "https://theneo.io/",
  "description": "AI-powered API documentation solutions for REST and GraphQL.",
  "location": "USA",
  "founded": 2021,
  "ownership": "Privately Held",
  "areasOfFocus": ["Api", "Developer Tools", "Artifical Intelligence"],
  "linkedin": "https://www.linkedin.com/company/theneoinc/",
  "analystScore": 75,
  "scores": { "analystScore": "750", "popularityScore": 342, "socialProofScore": 710 },
  "fundingSignals": [
    { "category": "INCUBATOR / ACCEL'R", "source": "Y Combinator", "url": "https://www.ventureradar.com/source/Y%20Combinator/047cccdc" }
  ],
  "milestones": [
    { "text": "Startup Battlefield Participant / TechCrunch Disrupt 2022", "date": "18 Oct 2022" }
  ],
  "summary": "Theneo (USA, founded 2021). Focus: Api, Developer Tools. 1 funding signal(s) on record."
}

A URL that cannot be collected returns a row with result_type: "error" and a plain-language error_message, so a failed input never disappears silently.

The dataset ships with two saved views: Company overview (name, country, founded, focus, analyst score, website, profile) and Funding signals (name, backers, milestones, founded, profile).

Pricing

Pay per result. One event, company-scraped, is charged once for every company profile pushed to the dataset. Nothing is charged for an input that returns no record. Current rates are shown on the Store card.

How to get started

1. View on Apify Store and click Try for free.
2. Paste one or more company profile URLs into Company profile URLs.
3. Run it. Results appear on the Output tab and export as JSON, CSV, or Excel. The Funding signals view shows backer provenance directly.

Profile URLs come from VentureRadar, the startup and emerging-company directory whose public profiles this API reads.

Prefer to start from code? The example repo has a Python quick-start plus MCP install walkthroughs for Claude, Cursor, and ChatGPT.

🔌 Use this API from Claude (MCP)

Add this Actor as a tool in Claude Code (free trial), Claude Cowork (free trial), Cursor, or any other MCP client through the hosted Apify MCP server:

https://mcp.apify.com/?tools=actors,docs,johnvc/ventureradar-company-api

With Claude Code (free trial):

claude mcp add --transport http ventureradar "https://mcp.apify.com/?tools=actors,docs,johnvc/ventureradar-company-api"

Then ask your agent something like "which of these startups have been through an accelerator".

Apify MCP integration docs: https://docs.apify.com/platform/integrations/mcp

💸 Pay per run with crypto (x402)

The VentureRadar Company Discovery API supports agentic payments via the x402 protocol. AI agents and MCP clients can pay for runs in USDC (on Base) with no Apify account or API token needed: point your agent at the Apify MCP server and it can discover, pay for, and run this Actor autonomously. Read the Apify x402 announcement for details.

Coverage, stated plainly

How much a profile contains depends on how much the source holds about that company. In live testing, an actively tracked startup returned 22 of 23 available fields, including funding signals and milestones. A long-tail company returned name, URL, and a popularity band, and little else.

That is normal for a startup database and it is worth knowing before you plan a large run: well-known and recently funded companies are rich, obscure ones are thin. Fields with no value are left out of the row rather than returned empty, so a thin profile reads as thin rather than broken.

🔌 Integrations: Build a Startup Database Pipeline

One run answers one question about one company. Most of the value shows up on the second and third run, because a profile picks up its accelerator batches and competition placings weeks after the company itself appears. The native Apify platform integrations connect this Actor to the tools you already run, and Apify handles the timing, so you do not need a server or a cron job of your own.

Tasks and schedules: keep a watchlist current

The pattern is one saved task per watchlist, one schedule across all of them.

1. Create a task. On the Actor page click Create empty task, paste the profile URLs for one theme (for example "climate hardware, seed stage"), and save it under a name you will recognize later.
2. Attach a schedule. Open Schedules in the Apify Console, create one with a standard cron expression, and add your tasks to it. 0 7 * * * runs every morning at 7 AM, 0 */6 * * * runs every six hours, 0 9 * * 1 runs Monday mornings. One schedule can trigger many tasks, so a single weekly sweep can cover every watchlist you keep.
3. Read the history. Each run appends fresh rows stamped with fetched_at, so fundingSignals and milestones accumulate across runs and you can diff last week's snapshot against this week's.

The published task Track New Milestones for a Startup Watchlist is this recipe already set up.

n8n

There is no dedicated community node for this Actor yet, so use the general Apify n8n integration, which runs any Actor and reads its dataset. A working shape for new-backer alerts: Schedule Trigger weekly, then the Apify node running johnvc/ventureradar-company-api with your watchlist, then a Filter node keeping rows where fundingSignals is present, then a Slack or email node sending companyName and summary.

Make and Zapier

Both have native Apify integrations, Apify on Make and Apify on Zapier, with Run Actor and Get Dataset Items steps. The same shape applies: fire on a trigger, run the Actor, filter on a field, then notify or store.

Supabase: keep your own copy

A watchlist is only useful if the history lands somewhere you can query. Supabase (hosted Postgres) is an easy target, and there are two paths.

• No code: in n8n, connect the Apify node to the built-in Supabase node and insert one row per company after each scheduled run.
• A few lines of Python: run the Actor and upsert the company rows into a table keyed on profileUrl.

from apify_client import ApifyClient
from supabase import create_client

apify = ApifyClient("YOUR_APIFY_TOKEN")
supabase = create_client("https://YOUR_PROJECT.supabase.co", "YOUR_SERVICE_ROLE_KEY")

run = apify.actor("johnvc/ventureradar-company-api").call(
    run_input={
        "companyUrls": [
            "https://www.ventureradar.com/organisation/Theneo/b40ae154-6867-456f-a215-d98fdae0048c"
        ]
    }
)

rows = [
    {
        "profile_url": item.get("profileUrl"),
        "company_name": item.get("companyName"),
        "website": item.get("website"),
        "founded": item.get("founded"),
        "location": item.get("location"),
        "areas_of_focus": item.get("areasOfFocus"),
        "analyst_score": item.get("analystScore"),
        "funding_signals": item.get("fundingSignals"),
        "milestones": item.get("milestones"),
        "fetched_at": item.get("fetched_at"),
    }
    for item in apify.dataset(run.default_dataset_id).iterate_items()
    if item.get("result_type") == "company"
]

if rows:
    supabase.table("startup_profiles").upsert(rows, on_conflict="profile_url").execute()

Filtering on result_type keeps error rows out of the table, and the upsert means a re-run updates a company in place instead of duplicating it.

MCP and AI agents

Apify exposes this Actor through the Apify MCP server, so an assistant in Claude Code (free trial), Claude Cowork (free trial), Cursor, or any other MCP client can call it as a tool. A question it can answer with live data: "of these twelve companies, which have been through an accelerator, and which one is oldest?" The published task Get Startup Company Data in Claude via MCP walks through the setup.

Webhooks

For anything custom, attach an Apify webhook to the ACTOR.RUN.SUCCEEDED event. Apify POSTs the run details, including the dataset id, to your endpoint whenever a scheduled run finishes, and your own service takes it from there: refresh a CRM, update a sheet, or push a digest to your team.

🔗 Related Tools and Actors

• Crunchbase Company API for funding rounds, amounts, and investor detail
• Startup Investors Data Scraper for who invests in whom
• Owler Company Intelligence API for revenue estimates and competitor sets
• PitchBook Company API for private-market financials

For contrast, the VentureRadar Similar Companies Scraper does a different job with a narrower output. It returns lookalike lists from a seed company name or a keyword tag, stopping at name, id, country, founded year, description, sectors, website, and scores. It does not return accelerator and incubator funding signals, dated milestones, or a per-URL error row, and its Store page shows a single-digit user count. It is the better pick if what you want is a wider net of names. This API is the one to use when you care who backed each company.

💡 Applications

Ready-to-run examples of this startup database API in action. Open any one and run it in a single click. Each starts from a public profile on VentureRadar.

Find Which Accelerators and VCs Backed a Startup

Pull the accelerator, incubator, grant, and award provenance behind a company, each entry with a source link. Run this task

Track New Milestones for a Startup Watchlist

Run a saved watchlist on a schedule and watch dated milestones such as accelerator batches accumulate. Run this task

Get Startup Company Data in Claude via MCP

Add the Actor to an MCP client and ask questions about companies in plain language. Run this task

Bulk Collect Startup Profiles from a URL List

Send up to 1000 profile URLs in one run and get one clean row per company. Run this task

Qualify a Startup Shortlist with Sector and Scores

Attach areas of focus, founding year, and analyst and social-proof scores to a shortlist you already have. Run this task

Export Startup Company Data to CSV or Sheets

Take a run's output straight into a spreadsheet or a downstream tool as CSV, JSON, or Excel. Run this task

FAQ

What is a startup database?

A directory of early-stage and emerging companies, with the sector, stage, and backing behind each one. This Actor turns individual profiles from one such directory into structured JSON you can filter and join.

How do I find early-stage startups by sector?

Collect a set of profiles and filter on areasOfFocus or keywords. Both are arrays, so a company can sit in several sectors at once.

Which startups have raised from accelerators?

Filter on fundingSignals. Each entry names the backer and its category, so you can select for incubators, accelerators, grants, or awards specifically.

How do I build a venture deal-sourcing list?

Start from a sector or an accelerator cohort, collect those profiles, then follow similarCompanies to widen the set. Founding year and analyst score give you a first-pass screen.

Does it return email addresses?

No. An email field exists in the source's own schema, but it was empty on every live record we tested, so it is deliberately not part of the output rather than being present and always blank.

Does it return funding amounts?

No. This source records who backed a company rather than how much was raised. For round sizes and investor detail, use the Crunchbase Company API.

Can I search by sector instead of supplying URLs?

Not in this Actor. The source offers no discovery endpoint, so you need profile URLs to start from.

Should I use an official API or a web scraper for startup data?

An API published by a directory is usually rate limited, quota bound, and gated behind a sales conversation. Web scraping gets you the same public information without a quota, but you own the parsing and the breakage. This Actor sits in between: it behaves like a clean endpoint you call with a list of URLs, and you pay per company returned rather than per seat.

Can I schedule this Scraper to run on its own?

Yes. Save your input as a task, then attach a schedule from the Actor's Actions, then Schedule menu. Cron works as you would expect: 0 7 * * * for daily at 7 AM, 0 */6 * * * for every six hours, 0 9 * * 1 for Monday mornings. One schedule can trigger many tasks at once, so a single weekly job can refresh every watchlist you keep. The Integrations section above has the full recipe, including where to put the results.

Can I integrate this Scraper with other apps?

Yes. Through Apify integrations the Actor connects to Make, Zapier, Slack, Google Drive, GitHub, and most other cloud tools. For anything not on that list, an Apify webhook on ACTOR.RUN.SUCCEEDED will POST the run and dataset id to your own endpoint. The Integrations section above has worked examples.

Can I use this startup database API programmatically?

Yes. The Apify API runs the Actor, schedules it, and fetches datasets over HTTP, and there is an apify-client package for both Python and Node.js. Ready-made snippets for this Actor are on its API tab, and the example repo has a runnable Python quick-start.

Can I use this Actor through an MCP server?

Yes. Add it as a tool in any MCP client through the hosted Apify MCP server with the URL https://mcp.apify.com/?tools=actors,docs,johnvc/ventureradar-company-api. It works in Claude Code (free trial), Claude Cowork (free trial), Cursor, and others. See the Apify MCP docs for client-by-client setup.

How else can I research startups and their investors?

Pair this API with the rest of the set. Crunchbase Company API adds round sizes and named investors, Startup Investors Data Scraper maps who invests in whom, and Owler Company Intelligence API fills in revenue estimates and competitor sets. Backer provenance here, money there.

Is this the official VentureRadar API?

No. This Actor is not affiliated with, endorsed by, or connected to VentureRadar. It reads public company profiles and is an independent tool.

Is it legal to collect startup directory data?

Collecting public data is generally lawful in most jurisdictions, though the rules differ by country and by what you do with the results. Apify has a plain-language write-up on the legality of web scraping. This Actor only reads profile pages that are already public.

What do I do if a run returns no results?

Check the URL shape first. A profile URL needs both the company name and the profile id, in the form .../organisation/<Name>/<uuid>; a name alone will not resolve. If the URL is right and the row still comes back with result_type: "error", read error_message, which says in plain language what went wrong. Thin output on a valid URL is usually the coverage effect described above rather than a fault.

🌐 About Alpha OSINT

This Actor is part of Alpha OSINT, toolset of financial and operations data sources and APIs. For support or requests for this actor, please start a ticket directly on our support page.

Last Updated: 2026.08.10