Technology

Training AI for Your Production Line

Generic AI models trained on internet videos or household tasks won’t understand your manufacturing environment. Your parts, fixtures, workflows, and production requirements are unique.

AIRA uses vision-language-action models that connect perception, task understanding, and control, combined with classical motion planning and safety constraints, trained using real operator demonstrations.

We employ three complementary training approaches that work together. Each method captures different aspects of your operation, building AI that understands your exact requirements and improves over time.

Simulation Training

Building and testing in virtual environments

We create accurate digital twins of your production line using facility CAD files and on-site scans. Your exact layout, dimensions, constraints, and equipment.

In simulation, we:

  • Train the AI on thousands of task variations without touching your production line
  • Test edge cases and failure modes safely
  • Iterate on motion planning and task sequencing rapidly
  • Validate performance before any hardware arrives at your facility

Simulation gives us speed and safety. We develop the core task understanding without disrupting your operations or risking damage to expensive parts and tooling.

Teleoperation demonstrations become training data. The AI learns from human expertise without requiring physical robot time or disrupting your production schedule. We can collect thousands of demonstrations quickly and safely, without waiting for hardware.

Teleoperation to Simulation

Human expertise captured in virtual reconstruction

Expert operators control simulated robots in your digital twin environment, demonstrating the exact techniques needed for your tasks. Pick this part this way. Position it with this orientation.

This captures human knowledge that’s hard to program directly:

  • How to handle part variations and tolerances
  • Recovery strategies when things don’t align perfectly
  • The subtle adjustments that experienced operators make instinctively
  • Task-specific tricks that work in your environment

Teleoperation in the Real World

Learning real-world physics and materials

Before deployment to your facility, robots are set up in a physical replica of your production environment at our site. Real hardware. Real parts. Real fixtures and tooling. Operators work through your tasks with actual equipment, capturing the physical interactions that simulation can’t fully replicate.

This replica phase captures:

  • Material properties and real-world physics that simulation approximates
  • Actual gripper-part interactions and contact forces
  • Real sensor data from cameras, force sensors, and proprioceptive feedback
  • Edge cases and variations in your actual parts

Within weeks, robots deploy to your production floor with AI that’s already been trained on real hardware and supervised by operators who understand your specific tasks. You get production reliability from day one, not months of debugging on your line.

The AI model improves week over week, while maintaining validated performance and safety constraints. Over time the model requires less supervision as it masters the specific conditions of your facility.

Supervised operation on your production floor

Once deployed, operators continue to supervise the robots remotely. When the AI encounters something unexpected, an operator takes control immediately. The task gets completed. Your line keeps running. Every intervention is logged and used to continuously improve the models.

This ongoing supervision captures:

  • Subtle environmental variations unique to your facility (lighting changes, temperature effects, vibrations)
  • Production-specific edge cases that only appear over time
  • How to handle the unexpected while maintaining your quality standards
  • Real production pace and rhythm

Continuous Improvement

Reliability day one

The three methods work together throughout deployment. Simulation provides safe, rapid iteration on core task logic. Teleoperation to simulation captures expert techniques efficiently at scale. Real-world teleoperation in the replica environment tests performance with actual hardware and materials before arriving at your facility.

Once in production, every task performed and every operator intervention makes the AI better. Edge cases get captured. Recovery strategies improve. The model learns the specific quirks of your production environment.

The Result: AI trained specifically for your manufacturing environment, backed by expert operators, delivering production reliability from day one and improving week over week.

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