"AI-powered search capabilities are continuing to work their way into toolkits as developers seek to speed up, optimize, and enhance their work. Fast-growing startup Perplexity has been a key player behind that push, and is now further bolstering its capabilities with a new search application programming interface (API). This gives devs access to the enormous web index, comprising billions of web pages, that powers the company's answer engine."
"Its indexing and retrieval infrastructure divides documents into sub-units that are scored against the parameters of the original query. This allows the API to return relevant, ranked snippets. This component is a stand-out for Mayham. "Instead of returning whole pages, they rank individual passages and blend keyword and semantic signals," he said. "That means better context for large language models and less messy preprocessing.""
Perplexity released a Search API that exposes a real-time index of hundreds of billions of web pages to developers. The API returns rich, structured responses optimized for AI workloads by dividing documents into sub-units scored against query parameters and delivering ranked snippets. The retrieval system blends keyword and semantic signals to improve context for large language models and reduce preprocessing. Users can filter results by region or date and access the service under a straightforward pricing plan ($5 per 1,000 requests). The API enables building retrieval-augmented generation, agentic workflows, and search products without manual scraping.
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