At minds.ai, we are driving the transformation of the semiconductor manufacturing industry through cutting-edge artificial intelligence and deep learning solutions. With a mission to maximize the potential of semiconductor manufacturing, we help fabs and manufacturers innovate faster, smarter, and with zero disruption to their existing workflows.
Founded with the goal of applying advanced AI to solve complex enterprise challenges, minds.ai began by tackling problems in industries such as pharmaceuticals, automotive, and business operations. This journey led to the development of DeepSim—a powerful, cloud-based AI engine that integrates proprietary and open-source technologies into a simple and stable platform.
Building on DeepSim, we developed minds.ai Maestro, a purpose-built solution designed to optimize operations and planning for large-scale semiconductor manufacturers. minds.ai Maestro is now helping industry leaders boost efficiency and unlock new levels of performance.
Headquartered in Santa Cruz, California, minds.ai operates as a global team of AI experts, engineers, and innovators. Together, we translate the latest breakthroughs in AI research into real-world impact for semiconductor operations worldwide.
We believe the future of semiconductor manufacturing lies in the synergy between human expertise and AI. With minds.ai, that future is already taking shape.
Transforming Manufacturing with AI Optimization
At minds.ai, we harness advanced AI to tackle complex enterprise challenges. From our beginnings in pharmaceuticals and automotive to our focus today on semiconductor manufacturing, we deliver precision, scalability, and efficiency.
Our flagship platform minds.ai Maestro® is a purpose-built software suite that optimizes large-scale semiconductor fabs.
minds.ai Maestro® – Smarter AI for Fabs
Maestro transforms fab operations through reinforcement learning, generative AI, and neural-network simulations—delivering real-time automation and decision support.
Deployed in leading fabs, Maestro helps:
• Maximize throughput and tool utilization
• Predict WIP (Work-In-Progress) more accurately
• Reduce queue time and operator workload
• Improve machine availability and cycle time accuracy
All deployments are secure, run either on-prem or in private clouds, and feature automated model updates via robust MLOps pipelines—without disrupting production.
Key Solutions in the Maestro Suite
1. Maestro Tool Model
Delivers real-time predictions for processing time and machine availability using attention-based neural networks. Results include:
• 50%–80% lower MAE
• 3%–7% higher utilization on bottleneck tools
2. Maestro Fab Model
Combines discrete-event simulation and neural networks to forecast WIP by layer, recipe, and tool group. Enables:
• Modular fab deployment
• “What-if” scenario testing
• Integration with dispatch and scheduling systems
3. Maestro RL-Optimized Scheduling
Uses reinforcement learning for real-time, adaptive fab scheduling. Supports:
• AI-assisted scheduling with engineer oversight
• Improved KPIs: throughput, idle time, queue constraint violations
• Reduced manual workload with no loss of control
Real-Time Results
Maestro reacts within seconds to live fab data, delivering continuous optimization, predictive insight, and measurable improvements in fab performance, without compromising reliability or control.
