Self-improving AI memory system with intelligent context injection and adaptive learning
Persistent memory toolkit for AI agents. Save context, recall insights, track decisions across sessions.
Structured memory system for AI agents. Context death resilience (checkpoint/recover), structured storage, Obsidian-compatible markdown, and local semantic search.
Extract and categorize insights from tweet links into structured notes.
Write-Ahead Log protocol for agent state persistence. Prevents losing corrections, decisions, and context during conversation compaction. Use when: (1) receiving a user correction — log it before responding, (2) making an important decision or analysis — log it before continuing, (3) pre-compaction memory flush — flush the working buffer to WAL, (4) session start — replay unapplied WAL entries to restore lost context, (5) any time you want to ensure something survives compaction.
Structured episodic memory with Q-value scoring. Remember what worked, forget what didn't.
Give your AI agent a brain that persists between sessions — and protect it from memory poisoning attacks.
Periodically reviews conversation history and writes memory files to maintain agent continuity across sessions. Dual-layer system with daily raw notes and curated long-term memory.
Generate structured meeting minutes from transcripts.