Compresr

Founded by Berke Argın in 2026

LLM-native context compression

Cost

Pay As You Go

Rating

★ Mixed Reviews

Time to value

Quick Setup (< 1 hour)

You can use Compresr to compress large amounts of text context before sending it to AI language models. It reduces the size of your prompts while keeping the important information, which cuts down on API costs and improves model performance. You can upload documents, compress conversation history, and route agent traffic through a proxy for better context control. The tool works with any LLM and integrates into existing workflows through their Python SDK.

What Compresr does

Install Python SDK and set up API keyUpload PDF documents to compression collectionsCompress conversation history before model callsRoute agent traffic through compression proxyGenerate compressed context for specific questionsIndex knowledge base documents for compressionMonitor API cost savings from context reductionIntegrate compression into existing AI workflowsCompresses context while preserving important informationWorks with any LLM through APIRoutes agent traffic through compression proxyUploads documents to named collectionsIntegrates via Python SDK in minutesQuestion-specific context compression algorithmReduces API costs by shrinking prompt sizeMaintains conversation state compression