$11 trillion of value is locked in granular IoT data. Let your business professionals unlock it!

From raw data to golden insights and gains instantly:

When your SMEs can easily uncover the secrets hidden in sensor data, you can save or make money, improve business efficiency, and create new data-driven products and services.

How to Enable IoT Analytics and Monetization Quickly

Learn from Small Data Samples

No big data required for model training. Start with the data you have today.

If you do not have enough data for machine learning, don’t worry. In many cases engineers store just one sample of what happened because people learn from one example. That is how machines should learn too as it is faster, less costly, and easily adaptable to changes. That is what we do.

Put the Human Expert in the Loop

Experts know; machines compute. Combine both strengths for faster, better results.

Machines can learn only what experts teach them. The human eye is superior to any machine in recognizing patterns and only the human brain can assign meaning to patterns. The man/machine loop enables faster, continuous learning and more accurate predictions.

Know the Language of Machines

IoT data patterns are signals. Do you have a dictionary for the decision makers?

Like human behaviors, machines generate a variety of signals. Different operating and environmental conditions produce different pattern signals. As your experts build sharable libraries of meaningful patterns, your organizational knowledge and abilities to act  on signals becomes a competitive advantage.

Monetize through Intelligent Monitoring

Monitor what you know and capture exceptions to learn what you do not know.

With Trendalyze pattern libraries and patent-pending artificial logical networks you can start monetizing your IoT data today and send alerts to engage your experts to enhance the process with newly occurring patterns. Continuous in-the-loop learning eliminates risks and grows the monetization opportunities.

Watch Our 2-Minute Explainers: How it works; how it differs?

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