Automation and integrations decision

Bardeen

A technical user can build a useful, narrower lead-sourcing and enrichment tool, but reproducing Bardeen’s maintained premium templates, enterprise compliance, and managed infrastructure is costly and outside the scope of a small DIY project.

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You pay

$10/mo

$120/yr

Read off the official pricing page.

You’d pay instead

$100one-off80 h to build

$120/mo12 h/mo upkeep

On cash alone, building overtakes the subscription at 13 seats.

Open-source builds that already do this

Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need - the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship. All Bardeen alternatives, with the arithmetic →

What a replacement has to do

  • Manually run scrapers to extract profiles, validate/enrich contact data, qualify leads with an LLM, and export results to a spreadsheet or CSV.

What it still won’t have

  • Enterprise SOC 2 / compliance assurances and managed certifications
  • Large catalogue of premium, site‑specific scraper templates
  • Maintained bot infrastructure and uptime guarantees
  • Built-in credit/usage system and team management features
  • Managed premium support and custom scraper services

What remains hard

  • Compliance and regulationEnterprise-grade security SOC 2 Type II, GDPR and CASA Tier 2 and 3 certified — so you can automate with confidence at any scale.
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 13 seats.

Paid seatsseats

Money you would actually spend

Keep paying
—

Subscription price × seats × 12

Build it
—

AI build —APIs + hosting —

Time you would spend

—

—

What you would spend

What we assumed

The verdict above measures whether you could build it. This one is only about money.

Runnable build prompt

Not run yet
Build a minimal self-hosted lead-sourcing microservice in Node.js (or Python) with: 1) a scraper module using Playwright to crawl search results and profile pages and extract structured fields (name, title, company, profile URL); 2) a connector to an email/phone validation API (configurable provider) to enrich and verify contacts; 3) an AI qualification step that sends extracted records to an LLM API (configurable endpoint + API key) and stores a quality score and reason; 4) export connectors to Google Sheets and CSV download; 5) a scheduler to run templates and a small web UI to start runs and view recent results. Out of scope: reproducing Bardeen’s large site-specific premium template library, SOC2 compliance program, team billing/credit system, and enterprise support. Include error handling for network failures, rate limiting, and HTML structure changes; include unit tests for scraper parsers and integration tests for API connectors; provide Dockerfiles and Terraform snippets for deploying to a single small cloud VM and managed Postgres.
How we checked5 sources · 3/3 runs agreed · evidence score 64

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 5 cited sources+3
  • Price verified on pricing page+3
  • 3/3 assessment runs agreed+4
  • Hard moats found in the evidence-3
  • Evidence score64

The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time - so the same evidence always produces the same number.

How scoring works →

Cited sources · 5

Every page the run actually retrieved.

Integrity checks

What held up, and what did not.

✓ Price read off the page✓ 3 independent runs, one answer✓ Citations limited to fetched pages! 1 moat quoted from the page