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Compresr provides context compression tools that trim large language model inputs to the most relevant information at both coarse and fine granularities. The service integrates via an API gateway to reduce token counts by up to 200×, lowering inference costs and latency while maintaining accuracy. It supports major LLM providers such as Claude, OpenAI, and Codex, enabling more efficient agent and application workflows.
Updated 2 months ago
Funding
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Founders
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Product
Features
- compresr provides research-backed context compression technology for Large Language Model (LLM) agents. Their models reduce token usage by up to 90% while preserving essential semantic meaning across various data types. This allows engineering teams to significantly cut LLM API costs through efficient context management.