How Digital Teams Are Adding AI to Industrial Operations Now

Digital teams are under immense pressure to modernise processes, integrate real-time data, and harness the capabilities of artificial intelligence (AI) via business-specific applications to deliver the tools, insights, and all-new capabilities needed to improve operations.

The potential to revolutionise every facet of industrial operations is within reach, but many teams face significant hurdles. This article explores how leading digital teams are overcoming these challenges and seamlessly integrating AI into their operations.

The Common Challenges Faced by Digital Teams When adding AI.

Digital teams in industrial businesses often grapple with several obstacles:

• Real-time Data: Your existing applications can't handle real-time data sources, which is critical for AI use within live operations.
• Integration Issues: Adding new data streams to current solutions can be cumbersome and costly, meaning you and your AI never has the full picture.
• Complex Operations: Off-the-shelf solutions often fail to meet the unique needs of complex industrial operations.
• Specificity: Each business unit is unique with different assets, data, systems, and use cases; which would lead to enormous system bloat if you were to adopt single, point-and-shoot solutions. 
• Adding AI to Legacy Systems: Upgrading legacy technologies to support AI and automation is seen as an impossible or expensive endeavour.
• Risk: Building custom applications is high-risk, expensive, and takes too long.

These challenges can stifle innovation and prevent digital teams, as well as their businesses, from realising the full potential of AI.

How Digital Teams Are Overcoming These Barriers: Custom Real-Time Data + AI Applications.

To navigate these challenges, digital teams can adopt integrated platforms that facilitate the deployment of AI across their operations via custom-built solutions, designed to perfectly fit your operations, processes, technologies, assets, personnel, and objectives.

The key to creating these bespoke solutions and their success relies on using platforms that offer:

• Seamless Integration: The ability to integrate with any existing system and process real-time data from multiple sources.
• Customisable AI: Platforms that allow businesses to train AI models on their specific data, enabling real-time recommendations and optimisations.
• Speed + Efficiency: Fast development and deployment of custom applications tailored to unique business needs.
• Affordability + Scalability: Solutions that grow with the business and offer a pay-as-you-go model, ensuring cost-effectiveness.

These are advanced, all-in-one platforms enable digital teams to easily integrate data sources from anywhere, analyse them in real-time, train and utilise automations and AI across all integrated technologies, and design front-end dashboards and interfaces for users - everything needed to create future-proof real-time data and AI applications, simply.

This technology is known as an integrated real-time data, AI + IoT platforms, but could also be seen to be a PaaS, IoT, AI, ETL, BI and integration platform all rolled into one.

Case Study: Transforming Pump Monitoring + Maintenance with AI.

A prime example of how digital teams are leveraging AI and these platforms can be seen in the case of a leading industrial business that implemented an IoT solution for pump monitoring and predictive maintenance.

This case study highlights the transformative power of integrating AI and real-time data:

The Challenge: The business faced frequent pump failures, leading to costly downtime and maintenance. Their existing systems couldn't provide real-time data or predictive insights.

The Solution: By implementing a comprehensive real-time data + AI solution, the digital team could monitor pump performance in real-time. They integrated various data sources, including legacy systems, and used AI to predict failures before they occurred.

The Outcome: The business saw a significant reduction in downtime and maintenance costs. The real-time data allowed for immediate response to issues, while the AI provided actionable insights and optimisations. For example, the team could ask the AI, "How can I improve energy efficiency?" and receive tailored recommendations based on their unique data.

You can read more about this here.

The Benefits of Adopting AI in this Way.

The adoption of integrated real-time data, AI + IoT platforms brings several benefits to industrial businesses:

• All-in-one, easy-to-use tool kits: they’re designed to have everything you need to initial develop a real-time monitoring solution, through to adding automation and AI capabilities.
• Speed to Develop + Deploy: Fast development cycles mean that digital teams can create and deploy custom applications rapidly, addressing specific operational needs.
• Integration + Real-Time Analysis Capabilities: The ability to process real-time data from any source, including legacy systems, ensures that businesses can make informed decisions quickly.
• Custom AI: Businesses can train their own AI models, tailored to their data and operations, to uncover optimisations and provide real-time recommendations.
• Automation + AI for Legacy Tech: The platform enables the use of AI and automation with existing technologies, transforming legacy systems without added costs.
• End-to-end solution delivery service + support: Platform providers, such as ourselves, offer end-to-end development, support, and scaling services; as well as self-serve options. Get help to get started or rely on them to deliver in perpetuity.

In an era where operational efficiency and innovation are paramount, digital teams are finding ways to integrate AI seamlessly into their operations. By overcoming traditional challenges with the right platforms, they are unlocking unprecedented efficiencies and transforming their businesses.

Rayven is an all-in-one real-time data, AI + IoT platform with unique industrial Generative AI and custom application building capabilities.

We deliver an easy-to-use, codeless toolkit that anybody can use to integrate, ETL and analyse all their data in real-time; build custom workflows and automations; leverage Machine Learning and predictive analytics; create, train, and deploy custom LLMs bespoke to their needs; and create the interfaces, alerts and reports that frontend users need to optimise, innovate and create.

Get everything you need to succeed with industrial Generative AI today and build custom AI applications fast and affordably: speak to us now to find out more and get started.