Enables 70-90% LLM API cost reduction by compressing conversation history via local Gemma 4 models or heuristics, featuring token counting, model routing, and pinned facts for preserving critical context.
Provides AI chat history compression tools through token-based trimming and AI-powered summarization strategies to manage conversation context within token limits.
Enables AI agents to compress and selectively retrieve context, with measured recall rather than claimed performance. It provides tools to assess potential traffic and token savings, list compression dictionaries, and assemble relevant memory entries within a token budget.
Provides intelligent code context and analysis through semantic compression, AST parsing, and multi-language support. Offers 60-80% token reduction while enabling AI assistants to understand codebases through local analysis, OpenAI-enhanced insights, and GitHub repository integration.