Pipeline Continuity
Every stage of the ML loop connects. Dataset to annotation to training to testing to live validation, with no manual stitching, no format conversions, no context loss between steps.
Your AI Connection.
IRVINEi Corporation was founded on a single conviction: the most impactful applications of artificial intelligence are not happening in research labs or cloud data centers. They are happening on cameras mounted in warehouses, on CCTV systems monitoring entry points around the clock. The physical world is where AI has to prove itself and it is the hardest environment to build for.
Every project exposed the same problem: the tools available were built for researchers running experiments, not engineers shipping products. Labeling happened in one tool, training in another, testing in a script, deployment in a separate system. When a model failed after deployment, debugging meant jumping across four different platforms with no shared context.
ALPEYE was built to fix that. It is the pipeline we needed and could not find. A single platform where dataset versioning, annotation, training, live validation and deployment are all connected steps in one continuous loop. Every feature was designed around a real problem we encountered shipping Physical AI models in the field. We made it available because every serious computer vision team is fighting the same battles.
Physical AI is machine intelligence applied to the real world: computer vision systems that see, understand, and respond to physical environments.
Unlike AI that runs in the cloud on clean data, Physical AI operates on noisy video streams, at the edge, in conditions no benchmark dataset replicates.
Every stage of the ML loop connects. Dataset to annotation to training to testing to live validation, with no manual stitching, no format conversions, no context loss between steps.
Our agents don't hide their reasoning. Every recommendation cites the exact metric or data point that triggered it. Engineers stay in control at every step. The agents accelerate decisions, not remove them.
ALPEYE is designed for teams who measure success by whether a model works on a live camera feed, not whether it scores well on a benchmark dataset. Every feature has a deployment answer: dataset health checks, confidence threshold tuning, live validation and client-ready PDF reports. Built by people who have shipped Physical AI models and know what breaks.
To give every engineering team building Physical AI the pipeline infrastructure they need to ship models that work in the real world: faster, with more confidence, and with the full reproducibility that serious deployment demands.
Learn About ALPEYE