Snipara
FeaturedAI Context Optimization
Snipara is an AI context optimization platform that retrieves and compresses relevant documentation, then delivers grounded, cited answers to reduce hallucinations in AI-powered workflows. Rather than running its own LLM, Snipara optimizes documentation to provide the most relevant context to users' preferred AI models.
Key Features
Everything you need to get the most out of Snipara.
Context Compression
Reduce 500K tokens to 5K relevant context per query with semantic and keyword-based hybrid search.
RELP Engine
Recursive decomposition breaks complex queries into focused sub-queries, handling documentation 100x larger than context windows.
Cited Answers
Every response links to source sections, eliminating speculative hallucinations.
Agent Memory
Store verified outcomes linked to source documents. Agents learn project conventions without re-tokenizing entire codebases.
GitHub Auto-Sync
Keep documentation indexed automatically on every push.
Multi-LLM Support
Works with Claude, GPT, Gemini, and other major AI models.
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