SearchCans

SearchCans offers a data infrastructure for AI workflows, providing real-time search results from Google and Bing and a Reader API that converts URLs into clean Markdown or HTML. The tool targets developers building AI agents, RAG pipelines, and knowledge workflows, delivering a unified API and a single credit pool. It emphasizes flexibility and scalable throughput through a concurrency model called Parallel Lanes.

The platform works by offering multiple APIs under one account: a SERP API for current search results, a Reader API for web-to-text extraction, and additional utilities like file extraction and web screenshots. Users authenticate with an API key and access a shared prepaid credit system.

Main capabilities include real-time SERP data in JSON, Knowledge Graph support, and the ability to extract source content into Markdown suitable for LLMs. It supports both Google and Bing SERPs and includes a path to convert various document formats into clean rendering.

Plans, platforms, integrations, or limits stated include prepaid credits starting with 100 free credits, no recurring subscriptions, and different Parallel Lanes levels that determine concurrent requests. It also highlights that there are no hourly caps and that concurrency scales through Lane Stacking.

Use cases

• AI agents and RAG pipelines needing current web context
• Retrieval-augmented generation workflows requiring Markdown or HTML output