About Minexa.ai

​

Where it comes from
Minexa started as a side project, built over several years out of a simple frustration: every new project meant rebuilding extraction logic from scratch, across thousands of sources, with tools that broke the moment a page changed.
 

The answer wasn't a smarter guess. It was a system that actually understood a page's structure, built before the LLMs were even a thing, out of an obsession with accuracy and universality. That's still the core of how Minexa is built today.
 

Gabriel, the founder, coded the extraction technology after years running large-scale scraping and data pipelines, for businesses across any industry: a $100M+ revenue research platform or data-mining systems spanning 12,000+ web sources for a major real-estate company. That's where the problem became impossible to ignore.
 

Minexa started in January 2022. It shipped first as a developer API. Since then, it's grown into a no-code platform too, the same engine, made accessible to anyone, straight into Excel or Google Sheets.
 

Connect on Linkedin 

​

Our mission

The fastest, most reliable way to turn web data into something you can build on: accurate enough for production, simple enough for anyone to use.

The web has the data. Getting it out reliably is the hard part.

Every site is different, and pages change constantly. At scale, small extraction errors become expensive fast.

​

Most extraction tools put an LLM between you and the data, asking it to interpret the page and infer the structure. Minexa reads the page's actual structure instead. No prompts, no probability, no hallucinated fields. Just the data that's actually there, extracted the same way every time.

​

What makes Minexa stand out

Built before the LLM wave, benchmarked against it

No maintenance burden:

• No selectors, no XPath, no CSS: Minexa reads page structure directly and adapts to it

• Train once, reuse indefinitely: it keeps working without retraining unless the site's structure fundamentally changes

• Schema-less by design: detects every meaningful data point on a page, no schema to define upfront

• Under 2 minutes to train a new page structure for a given site

Built to actually hold up in production:

• Automatic pagination and container detection: the page's real structure decides what gets extracted, not a rigid template

• Trained across multiple sample pages, not one: catches missing fields and variations before they become hallucinated or missing values

• Thousands of mathematical combinations tested per page structure to find the extraction path that holds up site-wide, not just on the page it was built on

​

Built responsibly

GDPR-compliant by design. Proxies sourced ethically.

​

​

​