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.
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.
Local-first, cross-session context store that reduces token usage by saving facts, decisions, and preferences, and recalling them in later sessions with token-efficient ranking and compression.