A purpose-built partnership to simplify the last mile of Edge AI deployment
Deploying AI on embedded and edge devices has historically been slow, fragile, and hardware-specific. Even when teams have strong data and capable silicon, getting a custom model to run reliably on a specific device can take months—or longer.
ModelCat and NXP Semiconductors partnered to eliminate that bottleneck.
Together, we enable NXP customers to generate custom, production-ready machine learning models fully optimized for NXP devices automatically. Models are delivered in three days or less and are validated on real hardware before deployment.
Why This Partnership Exists
NXP’s silicon portfolio powers millions of intelligent products across industrial, automotive, IoT, and consumer applications. But as AI workloads move closer to the edge, one challenge has become clear: Hardware capability is advancing faster than the tools required to build and deploy reliable AI on that hardware.
Traditional AI workflows weren’t designed for:
- Tight memory and power constraints
- Device-specific acceleration paths
- Real-world latency and reliability requirements
ModelCat fills that gap.
By integrating ModelCat’s AI-in-the-Loop model creation platform into NXP’s eIQ® AI software ecosystem, developers can move from data to a ready-to-run model without manual tuning, compilers, or trial-and-error optimization.
eIQ Model Creator
— Powered by ModelCat
eIQ Model Creator powered by ModelCat extends NXP’s eIQ AI software development environment with fully automated model creation and optimization.
Instead of manually building, tuning, and debugging models, teams can now:
- Upload prepared data
- Select a target NXP device
- Automatically generate a model optimized for that exact hardware
The result is a precision-fit model that accounts for:
- Device architecture
- Available NPUs and accelerators
- Memory footprint
- Execution speed
- Power consumption
All before deployment—before time, cost, and risk compound. This ensures models are production-ready the moment they reach the device, not months later.
What Happens After the Demo
After the demo, we can:
- Discuss your target hardware and use case
- Review whether ModelCat is a fit for your workflow
- Outline next steps for testing or onboarding
- Connect you with relevant partners or supported chips
No pressure. No generic pitch. Just clarity.
