E.N.G.R.A.M. is a graph-native memory engine that gives AI persistent, structured, confidence-scored memory. No more repeating yourself. No more forgotten context.
Traditional AI forgets everything between sessions. E.N.G.R.A.M. doesn't.
Memories are stored as typed, interconnected nodes — not flat text. People, events, preferences, and concepts form a living knowledge graph.
Every memory has a trust score. Repeated mentions increase confidence. Contradictions lower it. E.N.G.R.A.M. prefers omission over incorrect recall.
Combines semantic similarity with structural graph traversal. Finds not just what was said — but the context, relationships, and patterns around it.
Memories have timestamps and validity windows. E.N.G.R.A.M. knows when things happened, when they expired, and how preferences drift over time.
Session conversations are periodically summarized and merged into the persistent graph. Nothing important is lost — even across reboots.
Node-level access controls, role-based filtering, and sensitive data encryption. Your memories are private and protected.
ENGRAM follows the MemoryKeep whitepaper architecture — purpose-built for persistent AI.
Click the chat bubble in the bottom-right to start a conversation. Tell E.N.G.R.A.M. about yourself and watch it build memories in real-time.
Launch the full ENGRAM dashboard to explore your memory graph.
Launch Dashboard →