$SIBYL is building one of the missing layers for autonomous AI agents: persistent memory.
Agents that forget every session can’t run companies, manage workflows or improve over time.
Sibyl Memory gives agents durable, structured memory across sessions with real code, live products and a 95.6% LongMemEval score.
Very undervalued.
the living graph network is memory built for what comes next: large data sets, and networks of humans and agents working over them together.
every entry dated, traced to its source, sealed into a timechain that cannot be quietly rewritten. a swarm of agents keeps data current, so every reader, human or agent, can efficiently interact with current, quality data.
agreements are being drafted, and soon, two of our partners will begin testing with specialized prototype LGN's in prediction markets and robotics, respectively.
the goal is bigger than memory. combine LLMs, agentic frameworks, and living data that updates itself, and you create the conditions for emergent behaviors and real predictive intelligence. that is what we are building toward.
the record comes first.
SIBYL