Empowering Developers to Build Smarter, Faster Intelligence at the Far Edge
As the demand for intelligent, low-latency applications grows, developers are increasingly turning to AI solutions optimized for far edge, near-sensor applications. These solutions prioritize responsiveness, power efficiency, and compute constraints, and must be able to keep up with rapid changes in AI algorithms.
Lattice’s portfolio of edge AI FPGA hardware and software solutions simplifies the deployment of purpose-built, pre-trained AI models, making it easier to build and scale real-time edge intelligence for computer vision and audio applications in the automotive, industrial, and consumer markets. Lattice’s signature low power, small size FPGAs offer incredible life-long adaptability and parallel processing power. Having shipped over 50 million edge AI devices worldwide, Lattice provides a trusted path to scalable, low-latency innovation at the edge.
Want to learn more about Edge AI? Visit our What is Edge AI webpage.
Key Features
Purpose-Built, Pre-Trained AI Models
Pre-trained models for common vision and audio use cases reduce development time and effort.
Proven Global Adoption
Over 50 million edge AI devices shipped—trusted by leading developers and OEMs worldwide.
Multi-Platform Deployment Support
Run AI workloads across FPGAs, x86, and ARM CPUs, offering flexibility for diverse edge hardware.
Low Power, Low Latency Performance
Optimized for near-sensor applications where energy efficiency and real-time response are critical.
End-to-End Development Workflow
Use Lattice sensAI Studio to train, quantize, compile, and deploy AI models seamlessly.
Visualization Tool and SDK
Lattice Edge Vision Engine provides a visualization tool for Lattice's computer vision models and SDK.
Framework Compatibility
Seamlessly integrate your existing workflows using popular machine learning frameworks, including TensorFlow, Keras, and ONNX.
Ready-to-Use Reference Designs
Accelerate your development cycle with pre-built and tested reference designs that span diverse use cases.
