Support and discussions for the Sixfab Edge AI Expansion Board for Raspberry Pi 5: build complete edge AI systems with integrated DEEPX AI acceleration, NVMe storage, and LTE/5G connectivity.
Welcome to the Edge AI Expansion Board category!
This is your dedicated community space for discussing and building advanced edge AI systems for Raspberry Pi 5 using the Sixfab Edge AI Expansion Board. Whether you’re prototyping your first AI-powered device or deploying scalable edge infrastructure, this is where developers share real-world experience, ask questions, and optimize their systems.
What is the Sixfab Edge AI Expansion Board?
The Sixfab Edge AI Expansion Board is an integrated edge AI platform for Raspberry Pi 5, combining PCIe AI acceleration, NVMe storage, and LTE/5G connectivity in a single unified architecture. This makes it possible to run AI models locally, store data at high speed, and transmit results over cellular networks without requiring external hardware or cloud dependency.
By bringing compute, storage, and connectivity together, the platform enables developers to build low-latency, privacy-focused, and fully autonomous edge AI applications. It is especially useful for systems that need to process data in real time at the edge, such as vision-based AI, sensor fusion, and remote monitoring applications.
With a single under-board design powered via USB-C (which also back-powers the Pi 5), the system simplifies deployment while maintaining high performance and scalability. This makes it suitable for both prototyping and production-grade edge deployments.
What’s in the triple M.2 architecture?
| M.2 slot | Function |
|---|---|
 AI acceleration |
DEEPX DX-M1 NPU module, 25 TOPS at INT8, swappable |
 Storage |
NVMe SSD for high-speed data logging and AI pipelines |
 Connectivity |
LTE/5G cellular modem for always-on uplink |
How is it different from the AI HAT+?
The AI HAT+ is a top-mounted, AI-only accelerator ideal for prototyping. The Edge AI Expansion Board mounts under the Pi 5 and adds NVMe storage and cellular connectivity on top of the same DEEPX NPU ecosystem, making it the choice for connected field deployments. See the full comparison in the Raspberry Pi AI HATs category.
Topics covered in this category
- Building edge AI systems with Raspberry Pi 5 and hardware acceleration
- Using the Sixfab Edge AI Expansion Board for AI inference workloads
- Setting up PCIe-based AI acceleration and optimizing performance
- Working with NVMe storage for high-speed data logging and AI pipelines
- Integrating LTE/5G connectivity for remote and distributed systems
- Designing real-time computer vision and multi-camera applications
- Edge AI system architecture and deployment strategies
- Power management, cooling, and hardware optimization for edge devices
- Troubleshooting and performance tuning for production systems
What you can build
- Real-time computer vision and AI monitoring systems
- Autonomous robotics and edge intelligence platforms
- Smart city and infrastructure analytics systems
- Industrial automation and predictive maintenance solutions
- Distributed edge AI gateways with cellular connectivity
- Remote monitoring systems with local inference and cloud fallback
Products and resources
| Resource | Link |
|---|---|
 Buy Edge AI Expansion Board |
sixfab.com/product/edge-ai-expansion-board-raspberry-pi-5 |
 Documentation |
Overview · Specifications |
 Quickstart |
Edge AI Expansion Board Quickstart |
| Connectivity & storage |
Cellular Connectivity · NVMe Storage |
 Troubleshooting & FAQ |
Troubleshooting · FAQ |
| Model deployment |
Sixfab Model Zoo · DXNN SDK Workflow |
 DEEPX examples on GitHub |
github.com/sixfab/sixfab-dx-examples |
 All Raspberry Pi HATs |
sixfab.com/product-category/development-tools/raspberry-pi-hats |