Glossary

ATS Aggregator Data Layer

An ATS aggregator data layer is the discovery + extraction layer beneath HiringCafe-style job aggregators that turns Lever/Greenhouse/career-page SERP results into structured job listings (title, location, salary, requirements, apply URL) via dorked search + LLM-driven parsing rather than per-employer ATS API integrations.

Definition

An ATS aggregator data layer is the discovery + extraction layer beneath HiringCafe-style job aggregators that turns Lever/Greenhouse/career-page SERP results into structured job listings (title, location, salary, requirements, apply URL) via dorked search + LLM-driven parsing rather than per-employer ATS API integrations.

In Depth

Building a job aggregator the per-ATS-API way (Indeed Publisher, LinkedIn API, Greenhouse boards API) is gated, expensive, and slow. The hiringcafe-style approach uses dorked search ('site:jobs.lever.co company', 'site:boards.greenhouse.io company', 'site:company.com/careers') to discover live URLs, fetches each via search-API extract, and parses with an LLM. The data layer ships in a weekend; product effort goes into the ranking layer (which is the actual differentiator). Per-listing data cost is typically ~$0.005-0.02. The boolean filter problem (matching 'a/b testing OR growth OR CRO' inside the JD) is solved at the LLM-parse step, not at the search step.

Example Usage

Real-World Example

An r/hiringcafe post struggled to filter jobs by 'a/b testing OR growth OR CRO' across the entire JD. The data-layer fix: Scavio dorks for ATS URLs → /extract per URL → LLM-parse with the boolean criteria → filter to true matches.

Platforms

ATS Aggregator Data Layer is relevant across the following platforms, all accessible through Scavio's unified API:

  • google

Related Terms

Frequently Asked Questions

An ATS aggregator data layer is the discovery + extraction layer beneath HiringCafe-style job aggregators that turns Lever/Greenhouse/career-page SERP results into structured job listings (title, location, salary, requirements, apply URL) via dorked search + LLM-driven parsing rather than per-employer ATS API integrations.

An r/hiringcafe post struggled to filter jobs by 'a/b testing OR growth OR CRO' across the entire JD. The data-layer fix: Scavio dorks for ATS URLs → /extract per URL → LLM-parse with the boolean criteria → filter to true matches.

ATS Aggregator Data Layer is relevant to google. Scavio provides a unified API to access data from all of these platforms.

Building a job aggregator the per-ATS-API way (Indeed Publisher, LinkedIn API, Greenhouse boards API) is gated, expensive, and slow. The hiringcafe-style approach uses dorked search ('site:jobs.lever.co company', 'site:boards.greenhouse.io company', 'site:company.com/careers') to discover live URLs, fetches each via search-API extract, and parses with an LLM. The data layer ships in a weekend; product effort goes into the ranking layer (which is the actual differentiator). Per-listing data cost is typically ~$0.005-0.02. The boolean filter problem (matching 'a/b testing OR growth OR CRO' inside the JD) is solved at the LLM-parse step, not at the search step.

ATS Aggregator Data Layer

Start using Scavio to work with ats aggregator data layer across Google, Amazon, YouTube, Walmart, and Reddit.