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HighSNR
Less tokens, less noise — compress docs and RAG context
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@gskm
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About HighSNR
HighSNR is a context compression/denoising API that removes low-signal passages from long documents and RAG retrieval results before they reach your LLM. Send a document and a token budget, get back only the high-signal chunks. Fully deterministic, zero data retention, no AI model in the processing pipeline — runs fast on commodity CPUs.
Benchmarked on LongBench v1 with GPT-4o (200 samples): at 90% budget, beats full-context F1 on HotpotQA (71.57 vs 69.71) and retains 97.9% of full-context quality on Qasper. Budget is accurate end-to-end.
Free tier: 2M tokens, 14 days, no card required. LangChain integration available via pip. Self-hosted option in progress for teams that need data to never leave their network.
Product Insights
HighSNR provides a deterministic context compression API that reduces token usage for RAG systems by removing low-signal data while maintaining high retrieval performance. The platform offers fixed token budgeting and local privacy through a zero data retention policy.
- Deterministic processing that runs fast on commodity CPUs without internal AI model dependency.
- Proven performance on LongBench v1, exceeding full-context F1 scores on specific QA datasets.
- Developer-friendly integration via API and a dedicated LangChain package.
- Strict data privacy with zero retention and a self-hosted option currently in development.
Ideal for: Developers and Data Scientists building AI Agents or Chatbots who need to lower token costs while maintaining the accuracy of RAG context.
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