Scrape company data with AI — from query to lead list
To scrape company data you no longer need scrapers: describe the companies you want — sector, city, size — and Quantic AI searches three engines and Google Maps, opens each company's site and returns a structured list with names, websites, emails and locations. Pay only for pages that succeed.
$1 free every month · No card required · Blocked pages are never billed
# "coffee roasters in Portland — name, email, city" search("specialty coffee roasters portland") → 10 organic results · $0.0005 map("coavacoffee.com") → 77 URLs · found /contact · $0.0005 scrape("coavacoffee.com/contact", extract) → { "company": "Coava Coffee", "email": "[email protected]" } · $0.0002
How it works
The queries a researcher would run — automated
1 · Ask like a human
"Logistics companies in Rotterdam", "SaaS startups in Austin that are hiring", "specialty coffee roasters in Portland". Quantic AI expands the request into real search queries and runs them on Google, Bing, DuckDuckGo and Google Maps.
2 · Map every company site
Each company found becomes a map call: sitemaps and links reveal /contact, /about, /team and /careers in one request. The run above turned coavacoffee.com into 77 URLs — and knew exactly which one carried the contact details.
3 · Extract your fields
The relevant pages are scraped through residential exits with structured extraction: company name, email, phone, address — whatever columns you named. Output is validated, deduplicated across engines and sources, and typed.
4 · A lead list you own
The dataset lands as CSV or JSON — rows you can load into any CRM or sheet, with the source URL for every field. No seats, no export limits, no per-contact credits: it's your file.
Scrape business data from Google Maps and the open web
For local and physical businesses, Google Maps is the richest public index there is — name, address, phone, website, rating, reviews. The pipeline queries the Maps and Places verticals of the SERP API directly, then crosses the results with classic web search so online-only companies aren't missed.
Maps gives you the skeleton; each company's own site adds the flesh — emails, team pages, product lines. Merging both automatically is what makes the difference between a pin list and a usable company dataset.
Company emails without the shady lists
Contact vaults sell you addresses collected years ago and traded since. This pipeline reads them where companies publish them today: their own contact pages. Map finds the page, extraction pulls the address, the row records where it came from.
That keeps the data fresh and the provenance clean — role addresses straight from the source, with GDPR-relevant fields under your control from the first row. And walled platforms stay out of it: no LinkedIn logins, no scraped profiles, no gray-market enrichment.
Build a B2B lead list with AI, not a five-tool stack
The standard playbook chains a prospecting seat, an enrichment credit pack, an email finder and a spreadsheet of glue. Every hop loses rows and adds a subscription. Here the whole chain — find, visit, extract, dedupe — is one pipeline with one bill, the same AI web scraping service that powers every dataset on this platform.
And because the input is a prompt, your ICP can be as narrow as your niche demands — "3PL warehouses within 50 km of Verona" is a query, not a custom data project.
Prompt-built list vs a typical B2B contact database
| Quantic AI dataset | Typical contact database | |
|---|---|---|
| Collected | when you ask, from live pages | before you asked, decaying since |
| Scope | your exact niche, any geography | their filters, their coverage |
| Emails | from the company's public pages, with source URL | traded lists, opaque origin |
| Pricing | cents per run, pay per success | per-seat contracts, export credits |
| Ownership | your CSV/JSON, no limits | licensed access, export caps |
What does a 200-company list cost?
With Quantic AI (planned): 200 records × $0.03, emails and phones added only when found ≈ $12 with contacts. Building it yourself on the raw APIs: about $0.19 of unit prices — the developer path, code included.
Is scraping data legal or illegal?
Neither by default — it depends on what you collect and where from. Company names, websites, addresses and role emails published on public pages are generally fair to collect in most jurisdictions, while privacy laws like GDPR treat personal data with stricter rules, especially in the EU. Quantic AI stays on public pages and never logs into walled platforms. Prefer role addresses, honor opt-outs, and get legal advice for your market.
How do companies scrape data?
Usually one of three stacks: a browser extension for one-off grabs from a single site, in-house scripts (Python with BeautifulSoup or Scrapy) plus a proxy network to survive blocks, or a managed API that handles rendering and anti-bot for them. Quantic AI is the third kind with the discovery step included — it searches for the companies first, maps each site, then extracts, so nobody maintains per-site scrapers.
Can ChatGPT do web scraping?
Not reliably on its own. A model can read a page you paste in, but it has no proxy network, no anti-bot handling and no way to work through hundreds of URLs — browsing modes fetch a few pages and get blocked by the sites that matter. Give it tools instead: the QuanticData MCP server exposes search, scrape, map and crawl to ChatGPT, Claude or any agent, so the model drives a real pipeline rather than guessing.
Why not just use a free Chrome extension?
For one page on one site, an extension is fine. It breaks on the three things this job needs: finding the companies in the first place (there is no search step), handling hundreds of different sites with different layouts, and getting past bot walls without a proxy network. Extensions also run on your machine, from your IP, one tab at a time. Quantic AI does discovery, extraction and rotation server-side and hands back the finished file.
Can it scrape business data from Google Maps?
Yes. The pipeline queries the Maps and Places verticals of the SERP API — business name, address, phone, website, rating and reviews — then visits each company's own site for the fields Maps doesn't carry, like emails or team pages. One dataset, both sources merged.
How does it find company emails?
From the company's own public pages: map discovers /contact, /about and /team URLs, and extraction pulls the addresses published there — the run on this page found [email protected] exactly that way. No purchased lists, no guessed patterns sold as verified.
Can it scrape LinkedIn?
No. Quantic AI doesn't log into or scrape LinkedIn — walled platforms behind authentication are out of scope by design. It builds company lists from the open web: search engines, Google Maps and the companies' own sites, which is where the durable, legally cleaner data lives anyway.
What fields can I get for each company?
Whatever public pages carry: name, website, description, emails, phone, address, city and country, social links, and page-derived signals like careers pages or product categories. You name the columns in the prompt; extraction returns exactly those fields as CSV or JSON.
How is this different from buying a B2B lead database?
A lead database is a fixed vault collected before you asked, decaying since. Quantic AI collects at request time from live pages, scoped to your definition of the market — so a niche like specialty coffee roasters in Portland is as reachable as any Fortune-500 filter.
How much does a company dataset cost?
Two paths. Quantic AI, planned launch pricing: $0.03 per delivered record plus $0.02 per validated email and $0.05 per phone found — a 200-company list with contacts lands around $12. Or drive the raw APIs yourself at unit prices: the same list costs about $0.19, with the queries, extraction and merging as your code.
Do I need to know how to code?
No. Describe the companies and the columns; the dataset comes back as CSV or JSON. If you do code — or run an AI agent — the same pipeline is available as REST APIs and MCP tools today, with the identical pay-per-success billing.
Your market, as a spreadsheet
Start with $1 free every month — or join the Quantic AI waitlist for the full prompt-to-dataset service.
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