Vital alerts and information flow faster from the edge to the decision-maker because effective AI and ML models sit where data is collected.
Get AI where decision-making happens.
You know all that edge device data not in the cloud? We’re talking sensors, cameras and other monitoring solutions? We help you use AI and machine learning with them, so they can inform better, faster decisions.
Yes, the cloud is a fantastic place to aggregate IoT data and monitor it for trends. But sometimes you need information now. Moving your cloud-trained AI and machine learning models to the edge – next to where data is collected – enables near instantaneous decision-making right where the action happens.
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Greater cost savings
Your models work at maximum efficiency, minimising compute costs. And armed with new insight, you can make more money-saving decisions.
We accelerate the deployment of AI and ML models to the edge, so you can collect and analyse IoT data at cloud scale in a secure and consistent way.
Industrialise your AI and ML models to the edge.
Get models up and running alongside IoT data collection – fast
Thanks to our expertise in cloud-native MLOps, we help train and run your models with production workloads. You benefit from low latency and offline capabilities, with best-practice workflows and processes enabling more cost-effective and reliable model delivery to the edge. And that means you get cheaper and faster insight.
Scale up value from your IoT investments .
React to alerts and insight in real-time – while complying with data governance and security requirements
Embrace the power of open-source, cloud-native and secure AI and ML services alongside your IoT device landscape. Our approach is hardware agnostic, and gives you the benefits of AI/ML without having to transform data via the cloud. The result: more value from your IoT investments.
Get in Touch.
Let’s discuss how we can help with your cloud journey. Our experts are standing by to talk about your migration, modernisation, development and skills challenges.