Go beyond what is happening to what will happen with real-time predictive analytics.
Predictive analytics is critical if you’re to realize the full potential of IoT.
it uses many techniques, including: data mining, Data Science, modelling, and Machine Learning; to analyze real-time and historical data to make predictions about future outcomes.
For you, it means that you don’t have to wait for something to go wrong before you make improvements and can test optimizations before deploying them to see what will deliver the best results.
Accelerate delivery and reduce complexity
Launch Predictive Analytics and Machine Learning applications and see rapid business changing results.
Our codeless interface means that you can construct algorithms easily and then train and tune it, all without the need for a Machine Learning specialist.
Fast to build & deploy
Our simple drag-and-drop interface enables you to rapidly prototype your algorithm and go live with it in just a single click of the button.
Rayven’s IoT solutions come with pre-built Machine Learning algorithms, built by experts in the field that know your use case or industry intimately. From that, you can easily tweak and tailor them to meet your needs.
With no unnecessary consulting and development fees or coding, you can go from concept to delivery at minimal cost.
With your data united and immediately available for analysis, you can improve products, services or processes and realize continuous, incremental improvements into the future.
Real business outcomes
By combining predictive analytics with Internet of Things (IoT) technology, you can reduce costs, enhance productivity and improve your bottom line.
Rayven’s no-code Machine Learning Engine
Train, test and deploy new or ready-to-go Machine Learning models using our no-code Machine Learning Engine, which is built into our IoT platform as-standard. Utilizing it, you can detect anomalies, forecast production, predict failure, and much, much more.
Prepare your data
Select training data from your workflow and apply ready-to-go filters and normalizers that are natively available in the Machine Learning Engine.
Train your model
Select from a growing list of Machine Learning and Deep Learning models (e.g. change-point detection and LSTM) and run iterative training in the Machine Learning Engine.
Apply your trained models that have been built in the Machine Learning Engine (e.g. an anomaly detection model) to streaming data in the workflow and visualize it in your dashboard.
Alternatively, you can always bring your own model
Harness the value of your data, transform it into actionable insights, and drive immediate business outcomes.
Need help building a custom predictive analytics model?
Deploy in weeks, not months, with our ready-to-go process. Speak to us today to find out more.
Define your goals
We take your goals and identify the factors that influence it. This enables us to then establish where Machine Learning will be valuable and establish the data that’s necessary to collect to enable it to function.
We combine and integrate existing, historical, training, human-entered, static and real-time data flow into a single repository connected to Rayven’s IoT platform.
The next stage sees us creating visualizations and dashboards within the IoT platform to support pre-processing and simulation.
We conduct data validation, cleansing, sifting, decomposition, filtering, ordering, spectral decompression to determine what data is relevant, identify and fix issues, as well as establish parameters for ongoing data anomaly detection, validation and fixing into the future.
Data model development
With clean data, we can build a data model that the Machine Learning algorithm will be based on. This can either be using one of our pre-built industry or use case models, a custom built one for your business, or through importing your existing model.
With an established data model, we can build the Machine Learning algorithm based on your individual business’ set-up and desired outcomes.
We’ll deploy the model in our simulator and run it with your data to ensure that it’s been prepared correctly, the logic and algorithm is sound, and that the advice that it’s presenting will drive the right outcomes.
We’ll deploy all of the logic and models into your IoT platform. After ensuring it’s working as predicted, we can work with you on an ongoing basis to make adaptive improvements to the performance of the system based on client feedback or via the self-learning algorithms.
With your data united and immediately available for analysis, you can improve products, services, or processes and achieve continuous, incremental improvement over time.