Solutions
AI-based control that adapts to your environment
What We Do
We develop the mind for machines—adaptable perception, planning, and control that handle real-world variation.
Most automation today is either scripted or vision-only. Scripted automation breaks when parts, setups, or conditions change. Vision systems powered by AI improve detection, but still rely on rigid, pre-programmed actions that can't adapt when something goes wrong. MAD goes further: we apply AI across perception, planning, and control. This means robots don't just see — they decide and act. They adapt to variation, recover from errors, and keep production moving, reducing stoppages, rework, and the need for constant human intervention.
On-site data collection
Teleoperation and supervised runs in your environment.
Custom training
The right model for your task (diffusion policies, transformers, VLAs, world models).
Reinforcement Learning
We are integrating reinforcement learning into our training stack, combining it with teleoperation data to accelerate generalization and real-world robustness.
Deployment & iteration
Tuned to your KPIs—throughput, success rate, cycle time, quality.
Embodiment-agnostic
From simple machines to robot arms, mobile bases, etc.—the same learning stack adapts.
How It Works
Discovery (free)
Define task, constraints, clear success criteria, ROI targets.
Pilot
Collect data, train, demo on your line with clear metrics.
Deploy
Handover, operator training, monitoring, ongoing improvements.
Our goal is practical reliability: robots that can handle the vast majority of items in real-world conditions, with humans covering the rare edge cases — improving throughput without requiring rigid fixtures or perfect setups.
Why MAD
Fast iteration
Collect → Train → Deploy → Improve.
Safety first
Layered safeguards and stop conditions from day one.
Secure data collection
We use your production data to train models, always under clear agreements on privacy, IP, and benefits.
Ready to get started?
Book a discovery call to discuss your automation challenges