Implement Custom IIoT Applications Faster
Instead of time-consuming development projects, you can create customized reports for production experts in no time at all—from data integration to analysis!
A new question should not require a new software project
Business units need answers, while development teams prepare data access and analysis code. The IoT Data Hub drastically reduces this preparatory work.
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Too much preparation before analysis
Data access, cleaning, and visualization take time before your team can address the actual question.
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Custom logic requires development capacity
A special calculation or a new comparison waits for available coding capacity. Recurring tasks are implemented manually again.
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Isolated Applications as Time-Consuming Tasks
Data integration, visualization, and production analysis operate in separate systems, which regularly leads to coordination efforts and compatibility issues.
The right implementation for your question
Use dashboards for quick overviews, AI pipelines for continuous processing, and AI notebooks for custom analyses. The AI generates code that your team can review, customize, and reuse.
Which analysis would your team like to implement faster?
Conducting Your Own Analyses with AI Notebooks
For example, create a comparison of process values by product or time period. AI Notebooks supports data access, computation, and visualization with visible Python code.
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A platform you can extend
The IoT Data Hub is based on Apache StreamPipes, which we initiated. Device connectivity, storage, pipelines, dashboards, and charts are all integrated. AI pipelines and AI notebooks, as well as commercial support, complement the open-source foundation. Using APIs and SDKs, you can integrate existing applications or develop your own extensions.
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From workshop to a working pilot
Within a few days to weeks, we connect a production line and implement a suitable use case. Scope and data availability determine the timeline.
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Connect the first data sources in a workshop
Together, we select a production line and a specific task. We connect the first data sources during the workshop.
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Set up the production line and platform
We configure data collection, storage, and processing and map signals to machines and processes.
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Implement the use case
We develop the appropriate data preprocessing and analysis solutions, such as a dashboard or a custom analysis using AI notebooks.
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Assess the value during the pilot
Your employees will test the solution using live production data. We will evaluate the results against the agreed-upon goals, measure the benefits, and determine the next steps.
30-minute product demo
Bring your analysis question
In 30 minutes, we'll show you how to turn a technical question into an AI notebook or an AI pipeline, and how to review and reuse the results. No preparation required.