Enterprise-grade infrastructure for multi-agent coordination with four-layer memory architecture. Build AI systems that remember, learn, and collaborate.
Modern AI agents operate in isolation, losing context between conversations and failing to build on past work. Without persistent memory, teams duplicate effort, waste tokens, and can't scale complex multi-agent workflows.
Production-ready memory persistence for enterprise AI systems
Event logging, summaries, knowledge graphs, and vector embeddings work together to provide comprehensive context for every agent interaction.
Task delegation, handoffs, and completion tracking across specialized agents. Built-in coordination protocols ensure seamless collaboration.
Automatic summarization and compression reduces token usage by 95-98% while maintaining semantic accuracy through vector search.
Vector embeddings power intelligent context retrieval. Agents find relevant past work instantly, avoiding duplicate effort and building on existing knowledge.
Track token usage, context efficiency, agent health, and collaboration patterns. Built-in dashboards provide visibility into your AI infrastructure.
Battle-tested in production with automated backups, integrity validation, and self-healing repair systems. Enterprise-grade reliability.
From software development to entertainment
Coordinate multiple AI agents (Terminal, VS Code, Codex) to build production features. Agents hand off tasks, track progress, and avoid rework through shared memory of past decisions and implementations.
Persistent AI personas that remember past interactions, evolve over time, and maintain consistent personalities. Character relationships build naturally through shared memory and collaboration.
Learn how persistent memory can accelerate your AI development and reduce costs.
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