Make your IoT monitoring solution transformative by incorporating real-time predictive analytics.
Predictive analytics is critical if you’re to realize the full potential of IoT and craft an Industry 4.0 solution that will transform your organization.
Using Data Science, Machine Learning, and your data; you can create predictive models that know the future, meaning that you can fix machinery before it stops, test optimizations before deployment, and make instant improvements based on real-time performance.
Transform your organization and be Industry 4.0-fit.
Rayven’s platform enables you to simply and rapidly adopt predictive analytics which, when coupled with your real-time IoT monitoring and management solution, will deliver transformative, business-changing results.
Our code-less interfaces for both IoT solution and predictive analytics construction enables anyone (and any business) to build, deploy and optimize a transformative Industry 4.0 solution.
Fast-to-build & adopt
Our simple drag-and-drop interface enables you anyone to rapidly prototype algorithms and IoT solutions, test them to see what works best, and then go-live in just a single click of the button.
The Rayven platform comes complete with all of the functionality that you need to create a complete Industry 4.0 solution out-of-the-box, constructed by experts in the field that know your use case and the functionality that you need from the start. Predictive analytics isn’t an added extra.
With all the hard work already done by our developers, you can skip the consultants and platform development fees and go straight to concept and operational at minimal cost, making IoT technology and predictive analytics accessible to every business.
The Rayven platform enables you to unite all your data and make it available for analysis in real-time. Over time and as your algorithms learn more about your operations, you’ll get new insights that enable you to make continuous improvements – both manual and automatic – into the future.
By combining predictive analytics with Internet of Things (IoT) technology in your Rayven platform, you can quickly reduce costs, find optimizations and improve your bottom-line both measurably and demonstrably, rapidly.
Rayven’s no-code Machine Learning tool kit: AI Dynamix.
Create, train and deploy Machine Learning models into your IoT monitoring and management solution using the Rayven platform’s AI Dynamix feature. A modeller and engine programmable by anyone using drag-and-drop logic, it comes as-standard with the Rayven platform and enables anyone to adopt predictive analytics within their IoT solution.
Prepare your data
Select training data from your wider IoT solution and apply ready-to-go filters and normalizers that are natively available within AI Dynamix.
Create, import & train
Anyone can use AI Dynamix's drag-and-drop interface to create an algorithm from scratch or import another Python-based model, before running iterative training.
Deploy & predict
Deploy your trained model to streaming data in the Workflow Business Logic Modeller with a single click and visualize the results in your dashboard for real-time future insights.
Bring your own model. Rayven will support any Python-based predictive analytics model, including:
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.