VROC has expanded its product range as a response to customer demand and paradigm shift in the Industrial AI market.
- The end-to-end offering includes new generation enterprise data historian platform DataHUB4.0; Auto AI platform OPUS; smart cities / facilities platform OASIS, and engineered solution for data acquisition through DataEPIC.
Over time, VROC has seen firsthand the market shift from companies investing in internal IoT / big data enablement projects to ‘Solutions-as-a-Service’. This paradigm shift is attributable to Senior Executives demanding a quicker return on their investments. Three key challenges that paved the way to this fundamental change in approach are:
- Interoperability between system components.
- Need for more holistic asset management and workflow integration, to be able to understand the root cause of the problem rather than just the symptom.
- Model redundancy with manual modelling / re-modelling specifically for time sensitive / critical assets.
In response, VROC is pleased to announce that we have rebranded and expanded our product range to deliver solutions to address the key challenges. The new end-to-end product offering is designed to help customers acquire, store, access, visualise and analyse their compounding volume of data efficiently and cost effectively. The new product suite is designed to provide greater flexibility and scalability, that gives customers the control to rapidly design their own IoT enabled technology stack to quickly deploy their models into production at scale.
DataHUB4.0 is a new generation enterprise distributed historian, specifically built to ingest, and pre-process data for machine learning. With DataHUB4.0 customers can store all available data sources in one location, eliminating monolithic architecture, hidden licensing, maintenance, and support fees as well as per seat cost. Multiple users throughout the organisation can access historical and real-time data for live monitoring, analytics, and visualisations, without compromising data integrity and spending large amounts of time data- wrangling.
VROC’s leading Auto AI product, OPUS (meaning an artistic work on a large scale), enables organisations to rapidly produce no-code, dynamic, AI generated models for critical insights, predictions, and optimisation. OPUS is an automated AI solution that continuously learns from its environment, combining AutoML and MLOps in one product. It automates the tasks of building and operationalising predictive machine learning models in real-time and at scale.
OASIS has been designed for smart cities and facilities to centralise, remotely control, and monitor a wide range of assets including HVAC systems in buildings, roads, lighting, and water infrastructure, as well as equipment, and smart devices. Designed to be interoperable with disparate systems, OASIS significantly improves operator situational awareness by providing a holistic view of their assets and alerting them of abnormal situations in real time. Thereby maximising maintenance resources and optimising inventory and supply chains to achieve cost savings.
VROC’s data acquisition service DataEPIC provides the engineering, procurement, installation, and commissioning needs of customers to install hardware and software to enable data transfer from the asset to the data hosting platform of the customers’ choice.
“At VROC, we believe that the only way companies can become truly efficient is by seeing their organisation as a whole, looking at their assets holistically, and by breaking down information silos. With the advancement of automation and big data processing, it is no longer acceptable for companies to be spending a significant amount of money in time and resources to implement industrial AI at scale.” – Trevor Bloch, VROC CEO
The expanded range is designed to provide customers an end-to-end solution, from data acquisition, data storage, right through to advanced analytics and AI, and supports VROC’s vision of a world where industries are connected, integrated, and automated.
VROC is committed to tackling the most formidable AI adoption challenges around asset reliability and optimisation such as real-time integration with operational technologies for enterprise scale analytics, rapid model deployment at scale, sustainability, and maintenance, and whole of life cost effectiveness.
Established in 2016, VROC works with clients in process and discrete industries, primary industries, and smart cities / smart facilities.