If you want to receive an update when the open source library is published, sign up for the waitlist.
If you want to receive an update when the open source library is published, sign up for the waitlist.
HumxAI Reflex is being built for robotics teams deploying policies in changing, customer-specific environments. It turns failure context and human recovery into experience a robot can retrieve when a similar situation happens again.
The goal is practical adaptation at runtime: fewer repeated interventions, faster recovery from familiar failures, and structured experience that can later support robot learning and retraining workflows.
Record the execution context when a robot policy encounters an unexpected real-world condition.
Pair the failure trace with the human-guided correction and preserve it as reusable robot memory.
When a related situation appears, retrieve the resolved experience and guide the next action without changing the base policy weights.
Reflex sits alongside the existing VLA or robot policy. The base policy stays frozen while the memory layer listens for familiar failure contexts and supplies a bounded correction signal.
Store resolved failures, site context, task constraints, and customer preferences close to deployment. Similarity retrieval makes those experiences available when they become relevant again.
HumxAI Reflex is an open-source memory layer in development for robot policies. It is designed to capture failure context and human-guided recoveries so robots can reuse relevant experience when similar situations happen again.
No. HumxAI Reflex is designed to work as a runtime layer while keeping the base robot policy and its weights untouched.
The system records a failure and its human correction, stores that resolved experience, retrieves it when a similar context appears, and provides a bounded correction signal to help the robot respond.
The first open-source release is currently being built. Robotics teams and researchers can join the waitlist to receive a launch update.