Hosting: The Backbone of AI & RPA

In today’s?AI era, we constantly hear about?automation. From AI-driven workflows to?RPA, the focus is always on making processes more efficient. But there’s one critical piece that often gets overlooked:?hosting—the?infrastructure and environment?where these apps run, process data, and execute tasks.?

We’re familiar with different?hosting types, and on the surface, it all seems pretty intuitive. But when it comes to?hosting AI apps, the requirements are completely different from?traditional app hosting—and that’s something we don’t talk about enough.?

That’s why today, I want to take a closer look at the unique?requirements of AI hosting?through an interesting?SAP case study.?

The case study?

In this case, our client—a global?energy company?operating across multiple regions—needed to ensure that?business decisions?were based on the most?up-to-date information. The challenge? Centralizing?data sources?and?automating data entry?to speed up decision-making.?

To solve this, we used?SAP Cloud Platform?to host an?intelligent bot?that?automatically monitors data?entered every three hours via email. If it detects any?irregularities, it?immediately sends a notification?to the right people so they can take action and correct the issue.?

Why is hosting AI apps different from regular ones??

There is a tendency in the industry to think of the hosting process as standard and universal for all apps. However, hosting changes quite a bit when it comes to AI apps. They demand a specialized infrastructure, higher computational resources, and enhanced security compared to standard application hosting.??

For example, while traditional apps can run on basic cloud VMs or Kubernetes clusters, AI and RPA require environments optimized for heavy data processing, real-time automation, and integration across complex enterprise ecosystems. But let’s see this on the field with our intelligent bot.

The requirements behind hosting AI apps:?

• Scalability of Automation?

As the volume of data increases or the number of processes to be monitored expands, we need to ensure proper scalability to avoid performance degradation, delayed notifications, and failures in workload spikes. In other words, we must scale dynamically, which requires an environment that supports fast provisioning for our bot.?

• Real-Time Data Processing?

Since our bot must process incoming data in short periods of time, we need to ensure low latency to avoid bottlenecks or any delay in data validation that could impact decision-making or cause delays in notifications when errors are detected.??

• Data Integration Across Systems?

Because the client deals with data from various sources (databases, ERP systems, etc.), we must ensure that our bot can access and validate this data across different platforms. So, we need to integrate these sources into one cohesive automation process that contemplates both modern and legacy systems within the organization.?

• Monitoring and Continuous Optimization?

As our bot operates continuously, it’s important to monitor its performance, accuracy, and reliability. Over time, it will require retraining or adjustments to account for new types of errors or changing data formats, making ongoing maintenance crucial. Besides, we need to build failover mechanisms to avoid any process disruption.?

The results?

• Seamless integration of data across SAP systems, keeping information consistent and up to date.?

• Real-Time Data Processing for faster decision-making.?

• Automation of Data Search & Analysis?

• 45% Reduction in Response Times??

• 99% Reduction in Data Input Errors, lowering processing costs.?

• Real-Time Quality Information, enhancing analytics and decision-making.?

The problems behind business automations?

Our bot has proven its value by providing real-time insights for better decision-making and automating data monitoring tasks. However, this process doesn’t end in its deployment. These apps need continuous monitoring and scaling, and so do the infrastructures that hold them.??

So, hosting requires a long-term approach, balancing high computing power, integration, and security while adapting to evolving business needs. That’s why I think that the key to successful automation implementation is to build sustainable, scalable solutions that evolve with your organization.??

At Inclusion Cloud , we help businesses take this strategic approach. Let’s connect and lay the foundation for intelligent automation in your organization! And don’t forget to check the new edition of Axis for the latest business AI trends for 2025!?