OpenClaw architecture
An agent runtime built on OpenClaw, with multi-agent collaboration, extensible skills and plugins, tool use, automation, and connections across messaging channels.

A new standard for desktop AI agents


An agent runtime built on OpenClaw, with multi-agent collaboration, extensible skills and plugins, tool use, automation, and connections across messaging channels.
Brings vision, voice, and text together through real-time alignment and feature matching across diverse data sources, with an error rate below 0.1%.
Model compression and knowledge distillation keep the core model at just 5 MB and CPU usage below 10%, including on embedded devices.
Maintains over 95% decision accuracy with up to 30% noisy or adversarial data, backed by built-in fault recovery.
Supports distributed training across thousands of GPUs, sub-microsecond communication latency, adaptive load balancing, and training up to 200× faster than a single machine.
Federated learning and secure multiparty computation keep data private while enabling inference directly on encrypted information.
Put capable AI within reach
