BuiltIn Scraper: 17 Data Fields, Up to 1,000 Free Results/Month (2026)

Each record carries 17 fields, including the company name, industry tags, employee count, and hiring status. A thousand results cost $5.00 on the free-plan price, which you can cover entirely using the $5.00 monthly credit on Apify's free plan. The data identifies specific technology sectors like Fintech or AI and tracks workplace models across locations such as Austin, Seattle, and Chicago. This collector is for researchers and recruiters who need structured firmographics and hiring signals from the US tech market. It is not for those who need data from outside the United States, as the platform is US-centric.

Try it: open BuiltIn Scraper on Apify, sign in on the free plan and run the prefilled example.

Can you try BuiltIn Scraper before paying?

Yes. Apify's free plan includes $5.00 of prepaid usage every month and asks for no credit card. At $0.005 per result, that covers up to 1,000 results of BuiltIn Scraper a month, before run-start charges and platform usage.

The example request further down caps maxItems at 20, so a first run returns at most 20 results and costs at most $0.10 in result charges. That is enough to see the real shape of the data before deciding anything.

BuiltIn Scraper was last updated on 2026-07-02. It is one of 1,725 Actors CrawlerBros publishes on Apify, which together have 692,561 lifetime public runs and an average rating of 4.63 out of 5 across 416 reviews.

What does it cost to run BuiltIn Scraper?

Each result costs $0.005 on Apify's free plan, which is $5.00 per 1,000 results. Starting a run is charged separately at $0.005 per GB of Actor memory. Apify also bills the platform usage each run consumes, at the rates of your Apify plan, on top of these charges.

The maxItems control is the primary driver of your bill because result charges are applied for each company record written to the dataset. To keep costs low during initial setup, perform your first test with includeProfile disabled to verify the basic listing data before committing to the extra page loads required for full profiles.

How do you run BuiltIn Scraper from the API?

The schema marks 1 of its 6 controls as required: mode. Nothing in the payload below is illustrative. Those are the schema's prefilled defaults for BuiltIn Scraper, so the request works once your token is in place.

Call the synchronous endpoint to start a run and receive dataset items in one request:

curl -X POST "https://api.apify.com/v2/acts/crawlerbros~builtin-scraper/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"mode":"browse","location":"","officeType":"","companyUrls":[],"includeProfile":false,"maxItems":20}'

The same run from Python, using the official client:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")

run_input = {
  "mode": "browse",
  "location": "",
  "officeType": "",
  "companyUrls": [],
  "includeProfile": False,
  "maxItems": 20
}

run = client.actor("crawlerbros~builtin-scraper").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

And from Node.js:

import { ApifyClient } from 'apify-client'

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' })

const input = {
  "mode": "browse",
  "location": "",
  "officeType": "",
  "companyUrls": [],
  "includeProfile": false,
  "maxItems": 20
}

const run = await client.actor('crawlerbros~builtin-scraper').call(input)
const { items } = await client.dataset(run.defaultDatasetId).listItems()
console.log(items)

Because the call is synchronous, your client waits for the whole run. Keep it for exploration. For scheduled work, start the run without waiting and collect the dataset afterwards, so network trouble costs you a retry rather than the results.

Which BuiltIn Scraper inputs matter, and which can you skip?

The mode control defines whether you are browsing the directory by location or targeting specific entities via the companyUrls list. For most discovery use cases, focus on the location and officeType filters while leaving includeProfile as false unless you specifically need the website URL and founding date.

• mode (string): What to scrape. browse lists companies from the BuiltIn directory. byCompany fetches specific company profiles by name or BuiltIn URL. Default: "browse".
• location (string): Filter companies by US city/market. Leave empty for all US companies. Note: national uses the same builtin.com listing as "All US" (BuiltIn has no separate national-remote listing) - combine with officeType: remote to get remote-only companies. Default: "".
• officeType (string): Filter by work arrangement. Default: "".
• companyUrls (array): BuiltIn company URLs (e.g. https://builtin.com/company/stripe) or company names (e.g. Stripe). Slugs like stripe also accepted. Default: [].
• includeProfile (boolean): If true, fetch each company's full profile page for additional details. Slower but more complete. Default: false.
• maxItems (integer): Hard cap on total records emitted. Default: 50.

Fixed-choice controls: mode accepts browse (list companies from BuiltIn directory), byCompany (fetch specific company profiles); location accepts 9 values (default ""), including "" (All US (builtin.com)), chicago (builtinchicago.com), colorado (builtincolorado.com), boston (builtinboston.com); officeType accepts "" (All types), hybrid, on-site, remote (Fully Remote).

What does BuiltIn Scraper return?

The returned records are ideal for building firmographic lead lists and mapping regional tech ecosystems based on size and industry. They do not contain employee names or direct contact information, as the source focuses exclusively on company-level intelligence.

• name: Company name
• slug: BuiltIn URL slug
• builtInUrl: Direct BuiltIn company profile link
• logoUrl: Company logo image URL (browse mode, when the company has a logo)
• industries: List of industry/technology tags
• employeeCount: Number of employees
• officeCount: Number of office locations
• benefitsCount: Number of employee benefits listed
• isHiring: Whether the company is actively hiring
• openJobsCount: Number of open job listings on the company's profile (requires includeProfile or byCompany mode)
• websiteUrl: Company's official website URL (requires includeProfile or byCompany mode)
• founded: Year the company was founded (requires includeProfile or byCompany mode)
• headquarters: Headquarters location (requires includeProfile or byCompany mode)
• description: Company description
• sourceUrl: Source listing page URL
• scrapedAt: ISO 8601 timestamp
• recordType: Always "company"

These are the documented fields. Optional ones can be empty on a given record, so measure how often each field your deliverable depends on is populated across a real sample before automating the handoff.

How do you build the workflow end to end?

Open BuiltIn Scraper and work through these in order. Each step ends with something to check, so a bad configuration surfaces on a small run rather than a scheduled one.

1. Set the mode control to browse to crawl the directory or byCompany to target specific slugs in the companyUrls array.
2. Select a specific market from the location dropdown, such as austin or seattle, or leave it empty to search all US listings.
3. Adjust the officeType filter to hybrid, on-site, or remote to isolate companies based on their work model.
4. Enable the includeProfile toggle if your output requires the websiteUrl, headquarters, or founded year.
5. Enter a value in maxItems to limit the results; use 20 for a first run to stay within the $0.10 result charge example.
6. Execute the run and check the industries array in the dataset to confirm the companies match your target tech vertical.
7. Validate that isHiring returns a boolean value before exporting the final dataset for your recruitment or sales pipeline.

How do you apply it? Three worked playbooks

These are BuiltIn Scraper's own documented use cases, each worked through as an operating pattern rather than a description.

Use case 1: Talent acquisition

Outcome: Identify tech companies in a specific city that are actively hiring

Configure: Set mode to "browse", location to "chicago", and includeProfile to true.

Working method: Filter the results for records where isHiring is true and review the openJobsCount to gauge recruitment intensity. Use the benefitsCount to compare the competitiveness of different firms in the Chicago market.

Deliverable: A dataset of active hiring companies including job counts and direct BuiltIn profile links.

Stop condition: The isHiring field returns false for a majority of records in a known high-growth period.

Use case 2: Competitive research

Outcome: Map the tech company landscape in a market or industry vertical

Configure: Set mode to "browse", officeType to "hybrid", and maxItems to 500.

Working method: Perform a broad sweep of a market and aggregate the industries list to identify cluster density. Use the employeeCount to categorize companies into startup, mid-market, and enterprise tiers for competitive analysis.

Deliverable: A competitive map showing industry distribution and headcount tiers for hybrid-work companies.

Stop condition: The industries field is consistently empty for more than ten percent of the collected records.

Use case 3: Sales prospecting

Outcome: Build prospect lists of growing tech companies with hiring signals

Configure: Set mode to "byCompany" and populate companyUrls with a list of target firms.

Working method: Input specific company slugs and enable includeProfile to retrieve websiteUrl and headquarters. Evaluate the founded year and headcount to prioritize outreach to mature companies versus rapid-growth startups.

Deliverable: A prospecting list containing company headquarters, website links, and hiring status indicators.

Stop condition: The websiteUrl field is missing from the results for more than five targeted companies in a single batch.

What breaks, and how do you design around it?

The maxItems limit is 500 per run; to scrape larger datasets, you should run the Actor multiple times using different location filters. If a specific company is missing from browse mode, use byCompany mode with the exact slug found on the BuiltIn website.

When should you not use BuiltIn Scraper?

Do not use this Actor if you require global coverage, as BuiltIn focus is restricted to the US tech market. If you need crowdsourced intelligence like revenue estimates or lists of top competitors, Owler Scraper is the appropriate tool. For users who need deep salary benchmarks and editorial culture reviews for professional services like banking or law, use Vault Company Profiles Scraper. If your project requires the full text of job listings rather than just a count of open roles, Workable Jobs Scraper or SimplyHired Jobs Scraper provide the specific listing details that this scraper does not extract.

What should you check before trusting the output?

• Confirm that employeeCount is populated with an integer for firmographic segmentation.
• Verify the industries array contains at least one technology tag such as SaaS or Fintech.
• Check that websiteUrl is present in the output when the includeProfile option is enabled.
• Ensure the scrapedAt field contains a valid ISO 8601 timestamp from the current date.
• Stop the run if the result charge exceeds your budget for the expected number of company profiles.

None of this proves a record is correct. It gives a scheduled BuiltIn Scraper run defined points where it should stop instead of quietly passing bad data downstream.

Frequently asked questions

What is the price for 1,000 BuiltIn results?

On the free-plan price, 1,000 results cost $5.00. This is based on the $0.005 per result rate. Note that this figure does not include the run-start fee or platform usage charges, which vary by plan. You can test this using the $5.00 monthly credit included in Apify's free plan.

How can I get the website URL and founding year?

These specific fields are not included in the basic directory listing. You must set the includeProfile control to true or use the byCompany mode. This directs the Actor to visit the full profile page for each company, which is more comprehensive but takes longer to execute.

Can I filter companies by their tech stack?

The Actor returns an industries list that often includes technology tags like SaaS, AI/ML, or Cybersecurity. While there is no direct input filter for industry, you can filter the resulting dataset in your own tools using the values found in the industries array.

Does the Scraper require a BuiltIn account?

No login or API key is required. The Actor accesses public profile data that is available to any visitor on the BuiltIn website. It is designed to extract information from publicly accessible company pages and directory listings.

Why does the example run only return 20 results?

The example input has maxItems set at 20 to provide a low-cost introduction. This ensures the first run costs at most $0.10 in result charges. You can increase this value up to 500 in the settings when you are ready to collect more data.

Where to go next

When you are ready to run it, open BuiltIn Scraper on Apify; the free plan covers up to 1,000 results a month.

Start with the BuiltIn Scraper Actor page for the current input schema, pricing tier, and run history.

Other Actors we maintain for related data:

• Owler Scraper: Scrape Owler.com - crowdsourced company intelligence platform.
• Vault Company Profiles Scraper: Scrape Vault.com company profiles: salary data, rankings, benefits, departments, offices, and editorial company culture info for law, consulting, banking, and other professional-services employers.
• Workable Jobs Scraper: Scrape Workable job boards - search 50,000+ remote and on-site jobs globally, or scrape specific company boards by slug.
• LinkedIn Company Info Scraper: Scrape detailed company information from LinkedIn - description, industry, employee count, followers, website, headquarters, and more.
• Norway Brønnøysund Company Registry Scraper: Search Norway's official Brønnøysund Register Centre (Enhetsregisteret) for registered companies and organisations by name or exact organisation number.
• SimplyHired Jobs Scraper: Scrape job listings from SimplyHired.com - search by keyword and location, filter by employment type, remote work, date posted, and minimum salary.
• Site Researcher: Extract structured intelligence from any website: title, meta description, Open Graph tags, JSON-LD structured data, headings, images, videos, tech-stack fingerprint.
• karriere.at Jobs Scraper: Scrape job listings from karriere.at, Austria's largest job board.

Related guides:

• get in IT Jobs Scraper: Up to 1,000 Free Results a Month (2026)
• Naukri Scraper: 21 Data Fields, Up to 500 Free Results/Month (2026)
• ZipRecruiter Jobs Scraper Pro: 3 Practical Use Cases
• Vietnam Business Directory Scraper: 3 Practical Use Cases

Resources

• Actor documentation, input schema, and pricing: verified against the published Actor on 2026-09-29.

• Actor last updated by its maintainers on 2026-07-02.

• Run outcome figures cover the 30 day public window ending 2026-09-29.

• BuiltIn Scraper on Apify