Even though there are many advanced AI models, it is challenging to integrate them into current systems.
Limited interoperability among platforms restricts data utilization for AI models.
Operating in separate platforms for data handing and AI doubles management efforts and costs.
AI model integration and life cycle management requires extensive technical skills.
Time series forecasting comes with its own set of challenges, such as seasonality, outliers, trends, non-stationarity, and missing data. We provide a built-in model that users can run for forecasting without the need to train a specific model for their problem and deal with problems after deployment for real-time forecasting.
Our AI assitant will guide you for training of model. It will understand your problem and train models automatically without requiring expertise in Machine Learning.
CubedAI's standard protocols allow you to collect your data from different resources. You just need to copy our endpoint and add your devices' configuration.
Write your decoder function for saving data in clear format. CubedAI's built-in decoder function allow to save data from different resources in standart format for running ML models.
You can upload your own model or choose from trained model for real-time inference. When new data comes, our platform will run prediction or forecasting model in real-time.