The AIoT Engine is Fundamentum’s ML and AI service, constructed on the open-source Kubeflow platform and incorporating MLOps principles.
It enables you to efficiently develop, deploy, and manage custom machine learning models, adding value to your data. It converts your raw data into actionable insights and business-oriented values, optimizing your IoT infrastructure.
We leverage the flexibility and scalability of Kubeflow to orchestrate and automate your machine learning pipelines.
Management of the entire lifecycle of your ML models, from development to deployment and maintenance, with MLOps practices.
We eliminate all restrictions tied to specific application domains for any IoT use cases you envision, transforming raw data into significant business-oriented value.
With a single click, ensure your models are deployed on your IoT platforms with the correct parameters, allowing for rapid and efficient implementation that is always up to date.
We keep your models up to date by continuously retraining them with new data .
We automatically adjust your models for continuous performance optimization.
By analyzing performance trends and historical data using data-driven insights, cities can plan maintenance activities proactively rather than reactively. This optimized approach enhance operational efficiency and minimize disruptions. Predictive maintenance also reduces downtime, extends the lifespan of equipment, and maximizes budget allocation, ultimately leading to cost savings.
Collectively enable seamless device connectivity and management, advanced data analytics, secure communication, and robust reporting.
Ensure efficient and secure IoT operations while Fundamentum services support the development of your SaaS applications
