VROC, The AIoT Company

With Pi ProcessBook retiring soon, you might be surprised to discover that VROC's product DataHUB4.0 is a modern alternative. Whilst offering the same familiar functionalities as the legacy process historian, it also offers scalability, security, advanced analytics, and a modern interface. And, thanks to its rapid deployment and competitive pricing model, it is a logical next step. Don't be left out in the cold when support for Pi ProcessBook ends later this year, chat to us about how we can help you migrate now. Tag someone below who might benefit from this 👇 Discover more: https://bit.ly/3P0psEV #processhistorian #industrialanalytics #processengineering

Is scaling machine learning only possible with a massive team of experts? Many believe that to scale ML, you need an army of data scientists and data engineers. Which means significant budges, and development time. But that’s a myth. With advancements in AutoML and MLOps, you can automate complex tasks that previously required specialized knowledge and large teams. AutoML takes care of data wrangling, processing, training, and tuning, while MLOps streamlines the deployment and management of models. This means even lean teams can scale ML projects efficiently and effectively. Discover how your business could benefit using autoML and MLOps https://lnkd.in/gTPDu6kd At VROC, we’re empowering organizations to break free from the constraints of traditional scaling. Discover how you can do more with less. #MachineLearning #AutoML #MLOps #AI #DataScience #VROC

Every wondered how water processing and distribution networks might benefit from AI? Typically these networks are old and expansive, with high maintenance costs. Operators do their best to minimise disruptions to the public, and ensure compliance with health and environment regulations. There are five ways these water utilities and networks might benefit from AI: 1. Demand Forecasting 2. Predictive Corrosion 3. Predictive Clogging 4. Predictive Leakage 5. Predictive Performance Implementing AI in the water industry could lead to savings in maintenance operating expenditure and capital expenditure. Explore more about the benefits in our article: https://lnkd.in/gh39btz5 #waterutilities #watermanagement #aiot #digitalwater

Whilst VROC maybe a tech company at its core, did you know we also offer data science and digital transformation consulting services? Our team can work on bespoke problem statements, or alongside you and your team to engineer a fit-for-purpose solution. Pictured: Trevor Bloch at a recent consultation explaining how machine learning models predict future values for each and every sensor in a facility, and then provide valuable predictions of system performance. It's the future of manufacturing - AI helping engineers and operators maximise production. https://vroc.ai/ #datascienceconsulting #autoML #aiinmanufacturing #digitaltransformation #futureofmanufacturing

Tick Tock. Time is running out for PI ProcessBook users, with support ending in December. Good news, DataHUB+ is an alternative to ProcessBook and its default replacement, PI Vision. It can be rapidly deployed, connected to your existing process historian, or it can do the work of both your historian and data visualization software. (i.e. less subscriptions!). Learn more about how DataHUB+ compares to PI ProcessBook here https://lnkd.in/g8Xsszrs or get in touch with our team. #processbook #processhistorian #datavisualization

Look who we spotted escaping a rainy week in Perth, swapping it for sunny Kerteh Malaysia! Have a great week Juarez Lowe, Trevor Bloch, Siavash (Sia) Dosh, Ph.D. and Aik Leong Ooi presenting recent findings and recommendations to the team at PETRONAS Digital Sdn Bhd #AIoT #oilandgas #industrialai #futureofindustry #innovation #manufacturing Bumi Data Mining Sdn Bhd

Without a well executed data management strategy it is impossible for industrial manufacturers to harness the power of AI. We share why a data management strategy matters, and the six critical components that needs to be carefully planned and implemented as part of the strategy. Check out our latest article if you want to do more with your industrial data: https://lnkd.in/g3Ze-XWJ #datastrategy #datamanagement #industrialai #datapipeline #industrialdata #timeseries

A End-To-End Data and AI Pipeline. Do you know what it really means? We've broken it down into 5 simple components which make a world of difference when it comes to scaling AI. 1. Data Source - not limited just to structured data (goodbye SQL) 2. Data Storage & Pre-Processing - this is critical if you want AI to scale 3. Auto-Machine Learning - goodbye to coding models manually 4. Machine Learning Ops - we've automated it! 5. Continuous Insights - data insights that matter, in a timely fashion! Tag someone below that you think benefit from automating their data and AI processes 👇 Discover more here: https://lnkd.in/gMFpnpTV #mlops #autoML #aipipeline #datapipeline #industrialai #aiot

Over the past six months, our dedicated team has been hard at work enhancing our AI platform, OPUS. We’re thrilled to announce the latest release packed with new features designed to make your experience better than ever! The features of our latest release make our platform faster to deploy and the process of building models and visualization simpler. We know our users: 1) Aren't data scientists 2) Are extremely busy. That’s why these improvements are all about helping you extract valuable insights from your data effortlessly, ensuring your operations run smoothly. Discover the new features: https://lnkd.in/gEmkx6wu #nocode #VROC #IIoT #AIoT #modelops #modelbuilding #mlops #autoML

Let's talk Production Loss. It eats into margins and profitability, and for complex processes like Oil and Gas can accumulate quickly as a result of simple equipment faults and frequent maintenance activities. Thankfully AI is assisting operations and maintenance teams to reduce production loss, through continuous predictive insights and forecasting. One customer of ours experienced over 80% reduction in production loss across two of their late life assets. Read the case study here: https://bit.ly/3NKKXrH If production loss is eating into your bottom line it might be worth considering a new, data-led approach. #AIoT #AutoML #IIoT #oilandgas #complexprocesses #reliability