Neuracore

Deploy Robot Intelligence at Scale

Seamlessly deploy trained models to production environments, with options for cloud-based or on-premises deployment. Turn machine learning models into operational robot behaviors.

Deployment visualization

Deploy Robots In Minutes

Deploy robots that can cook, clean, or even dance. The possibilities are endless with our platform.

Key Benefits

How Deployment helps you accelerate robotics development

One-Click Deployment

Deploy trained models to production with a single API call, eliminating complex deployment pipelines.

Flexible Hosting Options

Choose between cloud-based or on-premises deployment depending on your requirements and constraints.

Low-Latency Inference

Optimized runtime for real-time robot control with ultra-low latency for time-sensitive applications.

Auto-Scaling Infrastructure

Automatically scale to handle varying loads, from a single robot to an entire fleet.

Comprehensive Monitoring

Track model performance, resource utilization, and inference metrics in real-time.

Continuous Improvement

Enable ongoing learning and adaptation through feedback loops and data collection from deployed models.

Deploy in Minutes

From trained model to production deployment in just a few steps

1

Select Your Model

import neuracore as nc

# Login to your account
nc.login()

# List available models
policy = nc.connect_local_endpoint(train_run_name="name of your run")

Choose a trained model from your account to deploy.

2

Connect

# Use the model for inference

nc.log_joint_positions(robot.get_joint_positions())
nc.log_rgb(robot.get_rgb())

prediction = policy.predict()
action = prediction.outputs[DataType.JOINT_TARGET_POSITIONS]

robot.execute_action(action)

Deploy your model and start using it for inference in your robot control loop.

Ready to Get Started with Deployment?

Join leading robotics teams already using Neuracore to accelerate their development. Sign up now and get $100 in free credits.