Owler Scraper — Company Data, Revenue, Competitors & Funding
Pricing
from $4.00 / 1,000 results
Owler Scraper — Company Data, Revenue, Competitors & Funding
Scrape Owler company data as clean JSON — revenue, employees, industry, HQ, competitors with proximity scores, funding & M&A. Affordable, no-contract alternative to Owler Pro / enterprise data APIs for B2B sales prospecting, lead enrichment, competitive intelligence & CRM data.
Pricing
from $4.00 / 1,000 results
Rating
5.0
(2)
Developer
Berkan Kaplan
Maintained by CommunityActor stats
1
Bookmarked
59
Total users
12
Monthly active users
3 days ago
Last modified
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Owler Company Intelligence 🦉
🎉 Turn Owler into clean, structured company intelligence — no login, no API key, one row per company, with firmographics, competitors, funding signals and news. Built for competitive intelligence, sales and market research.
🔍 What is the Owler Company Intelligence — and when should you use it?
Give this actor company names and it returns matching companies from Owler company-intelligence profiles — as clean, deduplicated rows you can filter, export or feed to an AI agent. Every run queries the source live, so the data is as fresh as the registry itself.
Use it when you need: a company company list for outreach; formation / status monitoring; or a canonical registry record for KYB and due diligence.
Use something else when: you need the official registry filing — this is an intelligence profile, not a government registry.
🤖 Use with AI agents
Already on the Apify MCP server? Ask for this Actor by name: foxlabs/owler-intelligence.
Your agent can pay for its own runs. This Actor is pay-per-event with agentic payments, so an agent can discover it, run it and settle the bill over x402 (USDC on Base) or Skyfire — no Apify account or API token of its own. Billing is the same either way: per delivered record, never for errors.
Otherwise paste this into Claude, ChatGPT, Cursor or any MCP-enabled assistant:
I want to pull company company records using the Apify Actor `foxlabs/owler-intelligence`.Input: `queries` is a list of company names. `maxResultsPerQuery` caps rows per query.Start with: {"queries":["undefined"],"maxResultsPerQuery":50}Ask me what to look up, run the Actor, then summarise the rows as a table.
The machine-readable API, MCP config and OpenAPI definition live at apify.com/foxlabs/owler-intelligence.md.
📋 Overview
Everything you need to turn Owler company-intelligence profiles into clean, structured data — in one actor, with no login, cookies or API key.
Why teams pick this actor:
- ✅ Whole source, one call — name or ID in, matching companies out.
- 🧹 No empty-promise columns — only fields this registry actually fills; degenerate columns are removed.
- 🔗 Stable identifiers — every row carries the source's own IDs, ready to join across runs and to other Fox Labs actors.
- 💰 Pay only for results — per-row pricing, empty/failed lookups never billed.
- 🤖 Agent-ready — MCP + x402 agentic payments.
✨ Features
- 🔍 Name or ID lookup — relevance-ranked name search or exact registry-ID lookup.
- 🏢 Full entity profile — status, legal form, formation date, address and the registry’s own contact fields.
- 🧹 Clean schema — deduplicated camelCase rows, ready for CSV/Excel/JSON.
🎬 Quick Start
curl -X POST "https://api.apify.com/v2/acts/foxlabs~owler-intelligence/runs?token=YOUR_TOKEN" \-H "Content-Type: application/json" \-d '{"queries":["undefined"],"maxResultsPerQuery":50}'
🚀 Getting Started (3 steps)
- Choose your targets — company names.
- Set the cap —
maxResultsPerQuerylimits rows per query. - Run and export — get a clean dataset as JSON, CSV or Excel.
📥 Input
{"queries":["undefined"],"maxResultsPerQuery":50}
| Field | Type | Description |
|---|---|---|
queries | array | Company names. |
maxResultsPerQuery | integer | Caps rows per query. |
maxConcurrency | integer | How many queries to fetch at once. |
includeRaw | boolean | Attach the source’s untouched record under raw. |
📤 Output
One row per company, saved to the dataset. Every row also carries query, scrapedAt, and — when a lookup fails — an error explaining why (never silently dropped, never billed).
| Field | Description |
|---|---|
url | Url |
name | Name |
legalName | Legal Name |
description | Description |
summary | Summary |
website | Website |
domain | Domain |
logo | Logo |
industry | Primary industry (NACE) |
industries | Industries |
industrySectors | Industry Sectors |
ownership | Ownership |
yearFounded | Year Founded |
headquarters | Headquarters |
address | Principal address |
phoneNumber | Phone Number |
exchange | Exchange |
ceo | Ceo |
leadership | Leadership |
employees | Registered employee count |
employeesFormatted | Employees Formatted |
employeesRange | Employees Range |
revenueAmount | Revenue Amount |
revenueFormatted | Revenue Formatted |
revenueRange | Revenue Range |
followers | Followers |
totalAcquisitions | Total Acquisitions |
totalInvestments | Total Investments |
acquisitions | Acquisitions |
investments | Investments |
firstInvestment | First Investment |
keyHighlights | Key Highlights |
momentum | Momentum |
fundingByYear | Funding By Year |
sicCodes | Sic Codes |
funding | Funding |
competitors | Competitors |
totalCompetitors | Total Competitors |
social | Social |
💼 Use cases
1. Competitive intelligence — profile competitors and their peers. Input: company names. Output: firmographics + competitors. Use: a competitor map.
2. Account research — brief sales on a target account. Input: company names. Output: company intelligence. Use: an account one-pager.
3. Market mapping — map players in a category. Input: company names. Output: competitors + signals. Use: a market landscape.
🔗 Integration
JavaScript / Node.js
import { ApifyClient } from 'apify-client';const client = new ApifyClient({ token: 'YOUR_TOKEN' });const run = await client.actor('foxlabs/owler-intelligence').call({"queries":["undefined"],"maxResultsPerQuery":50});const { items } = await client.dataset(run.defaultDatasetId).listItems();console.log(items[0]);
Python
from apify_client import ApifyClientclient = ApifyClient('YOUR_TOKEN')run = client.actor('foxlabs/owler-intelligence').call(run_input={"queries":["undefined"],"maxResultsPerQuery":50})for item in client.dataset(run['defaultDatasetId']).iterate_items():print(item)
Automation (n8n / Zapier / Make): schedule or webhook → HTTP request to the actor API with your queries → handle the JSON dataset → push to a sheet, CRM or dashboard.
📊 Pricing
Pay-per-event: per delivered record. Empty or failed lookups are never billed. View current pricing.
❓ FAQ
Do I need an account, login or API key? No. This reads Owler company-intelligence profiles.
What do I search by? Company names.
How current is the data? Every run queries the source live, so results are as fresh as the registry.
What does each profile include? Firmographics, competitor lists, funding and news signals as published on Owler.
Can I export to CSV / Excel / JSON? Yes — directly from the Apify dataset.
🐛 Troubleshooting
- Fewer rows than expected — raise
maxResultsPerQuery, or refine the name. - A name returns an unexpected entity — it matched a similar registered name; search the exact registry ID.
- No rows for a name — try the entity’s exact legal name or its registry ID.
⚖️ Is it legal to scrape this data?
This actor reads public company-intelligence profiles from Owler. Results can still contain personal data (e.g. a person’s name); personal data is protected by the GDPR and similar laws, so only process it with a legitimate basis. See Apify’s blog post on the legality of web scraping.
🤝 Support & contact
- 🌐 Website: data.foxlabs.com.tr
- 📧 Email: info@foxlabs.com.tr
- 🐛 Issues: open a ticket in the Actor’s Issues tab
- 🧰 More clean B2B data actors: Fox Labs on Apify
Changelog
1.9 — 2026-09-07
- Dropped empty-promise columns. Removed
ticker, revenueQuarterly— Owler company-intelligence profiles does not carry them, so they were shipped as always-null columns. Only fields this source actually fills are now emitted. - Enabled AI-agent payments (x402) + rebuilt the README to the full standard (What-is / when, AI-agents + x402 agentic payments + MCP, Overview, Features, Use cases, Integration, FAQ, Troubleshooting, Support & contact).
1.0
- Initial release: data from Owler company-intelligence profiles by name or registry ID.