Atriva simplifies edge AI video analytics with production-ready containers, multi-camera pipelines, and real-time intelligence.
Building Edge AI apps is complicated—requiring hardware tuning, optimization, deployment pipelines, and expertise across multiple domains. Atriva makes it simple. We provide ready-to-use containers, pre-optimized for your hardware, so you can skip the painful integration work. From setup to scaling, we streamline the entire stack—so you can move faster, cut complexity, and focus on creating impactful solutions.
Atriva simplifies the entire Edge AI lifecycle — from setup to deployment to scaling.
Choose from GPUs, NPUs, SoCs, or edge accelerators. Atriva supports any device.
Deploy optimized inference containers with zero manual setup.
Add pipelines, APIs, and monitoring as your workload grows — all with minimal overhead.
Six core advantages that make building and scaling Edge AI faster, easier, and more reliable.
Build once, deploy anywhere — our modular setup ensures long-term reusability across multiple edge AI projects.
Pre-configured Docker containers let you get AI apps running on edge devices in minutes, not weeks
Save on engineering and cloud costs with optimized hardware integration and efficient workflows.
Most of Atriva’s source code is open source — giving developers transparency, flexibility, and the freedom to customize without vendor lock-in.
Simple APIs, clear docs, and prebuilt SDKs make it easy to go from prototype to production.
Run on any AI accelerator — GPUs, NPUs, SoCs — without being locked into a single vendor.
Real-world applications powered by Atriva’s edge-optimized stack.
Run person detection, tracking, and attribute recognition at the store edge — no cloud dependency.
Deploy occupancy monitoring, anomaly detection, and access alerts on low-power edge devices.
Optimize robot navigation, perception, and on-device inference with Atriva containers.
Explore how Atriva powers real-world use cases—from retail analytics dashboards to license plate recognition portable to any hardware easily.
Atriva integrates seamlessly with popular frameworks, hardware, and AI runtimes. You bring your stack — we make it work together.
Atriva is powered by a community of contributors building the future of edge AI together.
All core components live on GitHub — transparent, forkable, and MIT-licensed.
Join discussions, contribute code, and collaborate with other builders.
Clear guides and examples help you get started quickly and build with confidence.
Join our community, explore the code, and help us shape the future of Edge AI.
