AgentQL
Query any web page in plain English — resilient data extraction and browser automation
AgentQL is a query language and toolkit for locating elements and extracting structured data from any web page using semantic, natural-language queries instead of brittle CSS or XPath selectors. It ships as a Playwright-native SDK, a REST API, and a browser extension, returning clean JSON that survives layout and markup changes because it matches on meaning rather than exact DOM paths.
We wire AgentQL into our data-engineering and automation stacks as the extraction layer that turns messy, unstructured web pages into reliable structured feeds. Using its Playwright SDK, we author semantic queries once and run them across sites that would otherwise need custom scrapers, then pipe the JSON into warehouses, enrichment jobs, and dashboards. Because AgentQL resolves elements by intent, our pipelines keep running when a target site ships a redesign — no selector rewrites, far less maintenance drift.
We pair it with our own orchestration and scheduling to run extractions on cadence, handle pagination and multi-step flows, and validate outputs against schemas before anything lands downstream. For automation work we drive AgentQL through real browser sessions so form fills, logins, and click-throughs target the right controls by description, giving us dependable end-to-end flows we can hand off to clients as monitored, production-grade jobs.
We build AgentQL queries that pull competitor prices, availability, and product attributes across dozens of retail and marketplace sites into a single normalized feed, refreshed on schedule to power pricing decisions and merchandising alerts.
We extract structured firmographic and contact signals from directories, review sites, and public profiles, then feed them into CRM enrichment and scoring so sales and lifecycle teams work from current, structured data.
We replace fragile in-house scrapers with semantic AgentQL queries that keep working through site redesigns, cutting the constant selector-repair work that makes traditional monitoring pipelines expensive to keep alive.
AgentQL matches elements by their semantic meaning — you describe what you want, like a price or an add-to-cart button, and it finds the right node. That makes extractions far more durable, since a class-name change or DOM reshuffle no longer breaks the query the way a hardcoded selector would.
Yes. We run AgentQL through Playwright browser sessions, so it operates on authenticated, JavaScript-heavy pages and drives multi-step interactions — navigating pagination, filling forms, and clicking through flows before extracting the structured result.
We validate every AgentQL response against an expected schema, add retries and change-detection, and run jobs on monitored schedules. Outputs land in your warehouse or CRM only after passing validation, so downstream systems get consistent, structured data.
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