CRM and sales decision

Leadbomb

A capable developer can build a smaller, useful replacement (search + scraping + SMTP verify + CSV) in ~40 hours using existing open-source scrapers, but reproducing LeadBomb's full multi-source coverage, scale, and polish is non-trivial.

Visit website

Built by Kevin Lee, who ships 3 products in this index

You pay

$17/mo

$204/yr

Read off the official pricing page.

You’d pay instead

$100one-off40 h to build

$20/mo6 h/mo upkeep

On cash alone, building overtakes the subscription at 2 seats.

No open-source build does this yet

Nothing published replaces this one, so a replacement starts from an empty file. Here is what it would have to cover.

What a replacement has to do

  • Search public sources for businesses/accounts, scrape public profile/contact pages, verify emails via SMTP, deduplicate and store results, export CSV.

What it still won’t have

  • Coverage of 15+ sources (minimal replacement implements only a few)
  • Polished UI/UX and bulk search polish (pagination, credit system, team seats)
  • Unlimited-scale scraping infrastructure and dedicated support
  • Built-in AI query expansion and other Pro features

What remains hard

  • Product polish and ongoing maintenance
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 2 seats.

Paid seatsseats

Money you would actually spend

Keep paying
—

Subscription price × seats × 12

Build it
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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 LeadBomb replacement using Python FastAPI, Playwright for scraping, Postgres for storage, Redis + RQ for background jobs, and a minimal React UI. Core features in scope: run keyword+location searches, scrape results from Google Maps + LinkedIn + Instagram (one social), extract emails, run SMTP verification, deduplicate, store leads, and export CSV. Out of scope: implementing 15+ source connectors, AI query expansion, billing/credits, team seats, and advanced UI polish. Include error handling, retry/backoff for scrapers, rate-limiting, basic tests for scraping and verification flows, and a Docker Compose setup for local deployment.
How we checked2 sources · 3/3 runs agreed · evidence score 60

How the score was reached

  • Partly verdict base52
  • 2 cited sources+1
  • Price verified on pricing page+3
  • 3/3 assessment runs agreed+4
  • Evidence score60

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 · 2

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 recorded