The Hog

Teams building AI agents and GTM workflows need context on companies, people, news, and social signals, but that data is scattered across separate tools like Exa, Clay, Apollo, and custom scrapers. Every team ends up stitching the same stack together from scratch, combining search, enrichment, scraping, and monitoring tools to get a full picture of a target. On top of that, most enrichment and research tools rely on cached data, so by the time an agent acts on it the signal may already be stale. This leaves developers maintaining fragile multi-vendor pipelines instead of focusing on their actual product.

The Hog is a unified API that lets agents search, enrich, monitor, and extract web data through one endpoint instead of five separate vendors. A single query on a company, person, domain, or keyword returns a structured object with funding, headcount, hiring, news, and sentiment signals, each tagged with its source and freshness and ranked by relevance. Results can be returned as JSON, Markdown, natural language, CSV, or XLSX, so they drop directly into agent workflows for research, lead enrichment, account monitoring, or competitor tracking. The pricing page shows metered endpoints for company search, people search, web search, social search, email and mobile verification, LinkedIn and social scraping, deepfake detection, deep research, and monitoring runs, billed per call with no seats or tiers.

The page frames this around AI agents moving fast while their underlying data layer still relies on scattered, cached sources that go stale before an agent can act on them.