Crawl the web,like a database query

with ~0 inference, ~0 hallucinations,& ~5 lines of code.

https://news.ycombinator.com

+ AT SCALE +

Same data, across pages and sites.

Teach Makra a page pattern once, then use it across listing pages, detail pages, and related sites. It follows the route, combines the results, and reuses what it learned as the catalog grows.

  • Pagination

    Makra can follow next links, page numbers, and infinite scroll. It returns the rows from the full list in one result, without a call for every URL.

  • Navigation

    A listing may only show a title and a link. Makra can open the detail page for the remaining fields and add them to the same record.

+ HOW IT WORKS +

Learn once. Reuse forever.

On a new page, Makra uses AI to map the fields and saves the result. On later visits, it reads the live page through that map. The values stay current, but the inference step does not repeat.

  • Cold path

    Makra maps the layout of a new page and stores where each field appears. Later requests use that stored map.

  • Hot path

    For pages with the same layout, Makra reads current HTML through the stored map. It does not make another AI call.

+ COST TO EXTRACT +

What does it cost to turn URLs into structured data? Compare one page with a 400-page run. Makra appears beside Firecrawl and Exa, which also read a URL and return structured results.

credits · converted to USD

+ ASK FOR MEANING +

Name the fields. Skip the selectors.

Tell Extract or Schema what the data means. Do not write CSS selectors or DOM queries. Makra matches your request to its page map and returns JSON in the requested shape.

  • Extract

    Give Makra a URL and describe the records you need. It finds them on the page and returns JSON, without asking you to point at HTML.

  • Schema

    Give Makra a JSON Schema with field names, types, and nesting. It fills that shape from the page, including lists and nested objects.

+ RESILIENCE +

When pages change, we follow.

Before Makra uses a stored map, it compares it with the live page. If a redesign changed part of the layout, Makra relearns that part and checks the extracted values against the page.

  • Algorithmic page structure verification

    Makra compares the stored map with the live page tree. When nodes move or disappear, it relearns the affected part instead of the whole page.

  • LLM-powered visual verification

    A visual check confirms that each extracted value appears where Makra says it does. It flags missing, empty, and misplaced fields before the result is returned.

+ IN PRACTICE +

Learn a recurring page layout once. Then turn the latest public web data into structured records, evidence, and change signals whenever you need them.

Product & price monitoring

Track prices, stock, and promos across the stores you care about.

Competitive intelligence

See price, feature, and integration changes from competitors.

GTM signals

Spot hiring, funding, and buying signals before you reach out.

Talent intelligence

Track open roles, skills, pay bands, and team growth.

Supplier discovery

Find suppliers by capability, location, and certification.

Web change events

Get an alert when a price, policy, or product changes.