CRM and sales decision
Lead Atlas
A capable developer can build a useful, pay-as-you-go local lead exporter (search, normalize, export, credits) in ~32 hours, but reproducing Lead Atlas' data coverage, freshness, and commercial-grade enrichment at scale is non-trivial and likely requires paid data sources or infrastructure.
Visit website↗Built by Faruk Durak, who ships 4 products in this index
Not priced
No pricing page we fetched carried a figure, so there is nothing to compare against. The build side is still real.
$100one-off32 h to build
$50/mo4 h/mo upkeep
No published price to break even against.
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
- User submits location+industry -> service queries external business data sources -> normalize & dedupe results -> present results and decrement credits -> export CSV/XLSX for outreach.
What it still won’t have
- proprietary aggregated data and scale (freshness/coverage)
- commercial-quality deduplication and enrichment pipelines
- enterprise/priority support and SLA
- any undisclosed data partnerships or proprietary sources
- legal/compliance work already done by vendor
What remains hard
- Product polish and ongoing maintenance
First-year cost
No published price
Lead Atlas does not publish a price we could read, so there is nothing to compare against. What building costs is below.
Money you would actually spend
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
Build a minimal Lead Atlas replacement as a single-developer project using: Node.js (Express) backend, PostgreSQL, React frontend, Stripe for payments, and Google Places API for business lookup; deploy on a single t3.small-equivalent host (or managed Heroku/Vercel) and store files on S3-compatible storage. Core features in scope: search by city/ZIP/radius and industry keywords; query Google Places (or other public APIs) and store raw results; normalize and deduplicate records (name, phone, website, address, email if present); credits ledger with one-time Stripe purchases and credit decrement per returned company; CSV and XLSX export; basic auth and account pages; logs and simple admin view to refund credits. Out of scope: proprietary data feeds, advanced enrichment (paid enrichment APIs), large-scale crawling, multi-tenant SLA guarantees, and enterprise integrations. Include error handling, unit tests for core normalization and credit logic, and deployment scripts.
How we checked
How the score was reached
- Partly verdict base52
- 2 cited sources+1
- 3/3 assessment runs agreed+4
- Evidence score57
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.
- official productLead Atlas — Local Business Leads by City, ZIP Code, and Industry
- official pricingLead Atlas pricing (Starter, Growth, Scale)
Integrity checks
What held up, and what did not.
