Industrial Cloud

The AI industry has seen significant progress in recent years, with an increasing number of successful AI projects. In 2019, 91% of AI projects failed to meet expectations (Deloitte), while by 2022, 54% had advanced beyond the pilot stage (Gartner). At Digitas Technologies, we regularly encounter several key challenges that impact the success rate of these projects:

Running AI/ML in production is hard. The processes are complex, the resources are sparse.
Feeding Sensor data to AI does not work out of the box. Without context and data alignment, AI is usually not capable of learning from the data.
Exceeding the budget. When starting from the scratch, the effort to set up all systems is always underestimated, resulting in unnecessary long-time to production.

Industrial cloud solutions illustration for AI and manufacturing Austria.

We address these shortcomings by offering a serviced solution based on AWS Cloud (Why Cloud?), drastically increasing the project efficiency for ML and data analytics projects while decreasing operational costs. In previous projects, we achieved cost reductions of over 80% and cut model development time by more than tenfold. Best of all, our fixed pricing ensures projects are predictable and easy to plan.

Diagram showcasing the integration of AWS cloud services with corporate infrastructure, highlighting scalability, data processing, and AI applications for industrial manufacturing.

Our industrial cloud solution gathers data from your on-premise system and processes it at high frequency, similar to a kappa architecture. The results are stored in a data lake for long-term use, like training AI models. We handle the data processing, including alignment and the application of AI models, to provide ongoing predictions about things like product quality, material wear, and yield. All of this data is then made available in real time through a visualization tool for your customers.

Such a solution is not an autonomous system. While we provide the infrastructure, you need to provide configurations and know-how. Your teams will have access to all data at rest and all machine learning models at all time. You remain in full control over your data.

You have full control over your data, with the ability to export, remove, or take over the services at any time. There is no vendor lock-in. We recommend that your analytics and data science teams take direct control of machine learning and visualization, as these are key to your business expertise.

Benefits of Our Cloud Setup:

High reduction in costs for model training processes.
Ready-to-use model performance monitoring.
Streamlined data access management.
No hassle with deploying production environments.
Accelerated model deployment process.

Why Cloud?

Cloud environments are sometimes viewed negatively, particularly in the process industry. However, with over 10 years of experience in developing and deploying AI use cases within this sector, we chose to focus on a cloud solution for the following reasons:

Scalability & Flexibility
All implemented subservices are built on scalable components, such as serverless functions, allowing you to pay only for what you use. This enables us to start streaming data from 100 sensor tags at a very low cost, and scale up to 1,000,000 tags at any time, without needing to redesign the architecture or incur upfront costs.
Security
All cloud providers invest heavily in security at a scale that would be unaffordable for a single company. Security measures and encryption are implemented at every layer. Additionally, you have full control over data access, allowing you to decide who can access which data.
Reliable Operations & High Availability
We use managed services for our infrastructure components, ensuring fault-tolerant, low-overhead operations. These services also provide high availability by utilizing system redundancy.
Pricing
All of these advantages come at a cost, but the services are still much more affordable than hosting them in-house. The main reasons are the economies of scale, which allow AWS to run infrastructure at a lower cost, and the consumption-based pricing model, where you only pay for what you use. There are no upfront costs, and you’re not locked into long-term commitments.

Our Project Plan

Data fabric manufacturing system showing seamless integration of production data across cloud platforms for optimized decision-making.

The project plan outlines the essential setup to get you started with our industrial cloud solution. Additionally, we offer a range of optional services, including support for developing your AI strategy and helping build and train your data science teams.

If you are intersted in a free consultation meeting or if you want to know how you could benefit from our solution, get in touch with us.

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