We build the core infrastructure for embedded intelligence. This phase focuses on developing our proprietary model optimization pipeline, creating reference implementations for target hardware, and establishing valid benchmarks. We prove that high-performance AI can run reliably on constrained edge devices without cloud dependency.

• Core model optimization pipeline
• Reference implementations (3-5 platforms)
• Edge-optimized benchmarking framework

With a solid foundation, we expand our hardware support and launch our OTA update infrastructure. We partner with key enterprise customers in industrial and consumer sectors to convert pilot projects into commercial deployments. This stage is about proving reliability at scale and providing the tools developers need to build on our platform.

• Expanded hardware support (10+ platforms)
• OTA update infrastructure launch
• Developer tools & SDKs

We scale to become the standard operating system for embedded intelligence. Our platform expands to include federated learning, multimodal capabilities, and global deployment. We aim for over 1 million deployed devices, establishing Zevion Labs as the critical infrastructure layer for the next generation of smart hardware.

• Global fleet deployment (1M+ devices)
• Federated learning capabilities
• Multimodal sensor fusion