CRM and sales decision

LeadX

A competent developer can build a useful local search/enrichment and export tool in ~40 hours using open-source CRM projects and search stacks, but LeadX's primary value is its proprietary, large-scale company/UCC/review datasets and export-credit + seat model which are not reproducible without significant data acquisition.

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Subscription$599/month ✓ verified
Initial build40 hours
Monthly upkeep3 hours + $200
Evidence3/3 runs agree

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 LeadX alternatives, with the arithmetic →

What a replacement has to do

  • Search company records, enrich with contact/UCC/review fields, and export enriched company/contact lists via UI or API.

What it still won’t have

  • Proprietary dataset coverage (LeadX claims "Searchable profiles for 11M+ companies")
  • UCC & lien intelligence breadth and curated filing signals
  • Integrated review and BBB signals at scale
  • Existing export-credit economy, seat management, and vendor support

What remains hard

  • Proprietary dataSearchable profiles for 11M+ companies
  • Proprietary dataLeadX connects company, contact, lien, web, and review data so revenue teams can identify the right accounts before outreach starts.
Read the build prompt

First-year cost

Keep paying

Paying ischeaper in year one.

On cash alone, building overtakes the subscription at 1 seat.

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 self-hosted minimal LeadX replacement: backend in Laravel or Node (Express), Postgres for primary storage, OpenSearch for full-text and faceted company search, React UI for search/enrichment/export, and simple API key auth. In scope: ingest a seed dataset (public business registries or a CSV), search endpoints (company search, URL/phone lookup), single-record enrichment view, CSV/bulk export with per-user credit accounting, basic seat support (1 user), deployment scripts (Docker Compose), CI for tests, and backups. Out of scope: matching the full 11M proprietary dataset, advanced UCC parsing at scale, and production-grade SLA. Include error handling, input validation, unit and integration tests, and a README with deployment instructions.
How we checked4 sources · 3/3 runs agreed · evidence score 64

How the score was reached

  • Partly verdict base52
  • An open-source build was found+5
  • 4 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 · 4

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! 2 moats quoted from the page