Failory Live Startups Directory Scraper

Scrapes the live startups directory on Failory — 14,000+ startups across 267+ country, city and industry facet pages. Returns startup name, website URL, industry, year founded, total funding, funding round and the facet each company was found under.

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Failory Scraper Features

• Walks every facet page — country, city and industry — in one run
• Returns 10 fields per startup, including total funding and most recent round
• Carries the facet slug on each record, so geography and sector come free
• maxItems: 0 pulls the entire directory

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What can you do with Failory startup data?

• VC and angel investors — Build a sourcing list filtered by geography and funding stage.
• B2B sales teams — Prospect recently-funded startups in a target sector, where budget actually exists.
• Competitive intelligence — Map every company operating in your category with funding context attached.
• Market researchers — Compare startup density and funding levels across cities and countries.
• Recruiters — Find funded startups in a region likely to be hiring.

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How Failory Scraper Works

1. The scraper enumerates Failory's facet pages — countries, cities and industries.
2. Each facet's startup listing is walked and parsed.
3. Every record is tagged with the facet slug it came from, which is where country, city and industry are derived.
4. Records stream to the dataset as they are parsed, stopping at maxItems.

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Input

A sample, for testing the shape:

{
  "maxItems": 50
}

The whole directory:

{
  "maxItems": 0
}

Field	Type	Default	Description
maxItems	integer	0	Maximum startup records. 0 scrapes all 14,000+

There are no facet filters — the run covers the directory and tags each record with its facet, so filter after the pull.

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Failory Scraper Output Fields

{
  "startup_name": "Veriff",
  "profile_url": "https://www.veriff.com",
  "main_industry": "Fintech",
  "year_founded": "2015",
  "country": "Estonia",
  "city": "Tallinn",
  "total_funding": "$92.8M",
  "funding_round": "Series C",
  "facet": "estonia"
}

Field	Type	Description
startup_name	string	Startup name
profile_url	string	Startup website URL, from Failory's directory link
main_industry	string	Main industry / sector
year_founded	string	Year founded
country	string	Country, derived from the facet slug where available
city	string	City, derived from the facet slug where available
total_funding	string	Total funding raised — e.g. $5.2M
funding_round	string	Most recent funding round type
description	string	Short description — not present on list pages, so usually empty
facet	string	Facet slug the startup appeared under — e.g. estonia, fintech, london

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FAQ

Can the same startup appear more than once?

Yes. A company listed under both estonia and fintech produces one record per facet, each tagged with its own facet value. Deduplicate on profile_url if you want one row per company.

Why is description empty?

Failory does not publish descriptions on its directory list pages, and nothing is invented to fill the field. It is emitted for schema stability.

Does profile_url point to Failory or to the company?

The company's own website, as linked from Failory's directory.

Is total_funding exact?

It is what Failory publishes — usually a rounded figure like $5.2M. Treat it as an indication of stage, not an audited number.

How long does a full directory pull take?

It covers 267+ facet pages and 14,000+ records. Start with a small maxItems to confirm the shape before setting it to 0.

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Need More Features?

Want facet filters at query level, or deduplicated output? Open an issue on the actor.

Why Use Failory Scraper?

• Funding stage on every record — Total raised and most recent round, which is what turns a company list into a prospect list.
• Geography and sector come attached — The facet tag means no separate enrichment pass to know where a startup is or what it does.
• Pay per record — Sample 50 or take all 14,000 and pay for exactly what comes back.