If you've ever needed to go from a company's website to clean, structured data — its name, sector, a short description, social links, a contact email, and the technologies it runs on — you know the options aren't great: #
Build your own scraper. Brittle, and every site is different. You'll spend more time maintaining selectors than using the data. #
Pay a heavyweight data provider. Expensive, and the data is often a stale snapshot from months ago. #
Paste HTML into an LLM and pray. Sometimes you get valid JSON. Sometimes you get a hallucinated CEO email that doesn't exist.
I kept hitting this wall while working with lists of company domains, so I built a small API that does one thing well: send a company URL, get back clean JSON.
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The two rules that shaped it
1. It reads the live site at request time. Not a database snapshot from last quarter. If a company rebranded yesterday, you get today's version.
2. It never guesses. This was the hardest constraint to enforce with an LLM in the pipeline. Missing fields come back as null
— never invented. If there's no contact email on the site, you get "email": null
, not a plausible-looking fake you'd import straight into your CRM.
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What a call looks like
And the response:
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How it works under the hood
A few design decisions, for the curious:
Two-pass tech detection. A fast pattern-matching pass first (think Wappalyzer-style fingerprints), then an LLM enrichment pass only for what patterns can't catch. Cheaper and faster than going full-LLM on everything. #
Hard content trimming before the LLM. Page content is capped before any model call. This keeps latency and cost predictable instead of exploding on heavy JS-rendered sites. #
Caching with a 14-day TTL. Repeat lookups on the same domain return in ~200 ms instead of re-scraping. The cached
field in the response tells you which path you hit. #
Strict schema validation. Every response is validated against a strict schema (Pydantic v2) before it leaves the API. Either the JSON conforms, or you get a proper error — never half-broken output.
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Use cases I built it for #
Lead enrichment: turn a list of prospect domains into CRM-ready records. #
Tech-based targeting: filter prospects by their stack ("show me companies running Shopify"). #
Data hygiene: verify and refresh company records against the live web instead of stale databases.
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Try it There's a free tier (100 requests/month), enough to test it against your own data:
👉 AI Live Company Enrichment & Tech Detector on RapidAPI I'd genuinely love feedback from other builders — on the positioning, the pricing, and especially: what field would you want it to extract next? Drop a comment below.