GPT-Zip.Link

Building RAG (Retrieval-Augmented Generation) pipelines with raw web content means bloated token counts, slower responses, and higher costs. GPT-Zip.Link solves this by intelligently compressing web content before it hits your prompts — combining content-aware HTML stripping, CSS and JavaScript removal, whitespace elimination, and LLM-powered language compression to reduce input tokens by up to 87%.

The result is leaner, faster prompts that cost less to run without sacrificing the information your model actually needs. Whether you're a developer optimizing an AI application or a researcher working with large volumes of web data, GPT-Zip.Link makes your RAG workflow dramatically more efficient.