下一代认知多智能体系统
We are building an autonomous workspace utilizing Partially Ordered Sets (Poset) for context compression, reducing software engineering API costs by 10×.
Powered by cutting-edge research in order theory, cognitive science, and distributed systems.
Leverages Partially Ordered Sets to structure and compress multi-agent context windows, eliminating redundant tokens.
Autonomous agents collaborate through a self-organizing mesh topology with real-time knowledge synchronization.
Dynamically routes prompts across model tiers, ensuring optimal quality-to-cost ratio for every engineering task.
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