Innovate at scale with IoT and Data Science

Develop your own IoT solutions on one collaborative platform

With the Record Evolution platform you can manage IoT devices worldwide, gather data and deploy machine learning algorythms.

In 3 steps to your own IoT solution

Step 1

Create a common platform for your teams.

Everything begins with the right tool. With the Record Evolution platform you bring your experts—from engineers to data scientists—together in one place.

Speed up your IoT development by minimizing communication gaps and making processes transparent. The platform takes care of all the technical details so that you can fully concentrate on your solution.

Connect your IoT devices and collect data.

Step 2

Connect your IoT devices and collect data.

Bring your machines and sensors to the platform from any location worldwide. Develop your own IoT applications. Make them available as packages in real time on any number of IoT devices to collect initial data.

This is how you create a long-term basis for the iterative development of IoT solutions for many possible application scenarios.

Step 3

Analyze data and develop your machine learning solutions.

Use a customized application to collect data from your IoT devices and other sources. Manage these on a comfortable user interface that is specially designed for the needs of engineers and data scientists.

Train machine learning models and roll them out as applications on your IoT devices in just a few steps.

Analyze data and develop your machine learning solutions.

Start today.

Register for free or contact us to discuss your case.

Collaboration

For everyone working with data

At Record Evolution, we foster a culture of collaboration in the work with devices and data. Join our growing community!

Manager of IoT and Data Science projects

Managers

👍 Distribute access rights and keep track of the progress of your projects.
👍 Benefit from simplified reusability and automation.
👍 Save resources and costs with machine learning solutions.

Data scientists

👍 Develop ML models in integrated workbooks with native PostgreSQL or Python based on the data collected by your engineers.
👍 Make ML models available to engineers for use on IoT devices.
👍 Create automations quickly and easily.

Business analyst working on IoT and Data Science projects

Business analysts

👍 Integrate sensor data into the tools of your choice and enrich them with additional data.
👍 Develop custom queries on data models using PostgreSQL or Python.
👍 Generate analyses and live presentations quickly and easily. Provide your data scientists and managers with customized analyses and dashboards.

Engineer working on IoT projects

Engineers

👍 Work with the programming environments and protocols of your choice to make data available to your data scientists.
👍 Monitor and manage IPCs and applications from a central location.
👍 Use the devices and sensors that convince you.

Why the Record Evolution platform?

We create a space where data teams easily build solutions with machine learning and IoT.

Flexible IoT development

Work together in connecting IoT devices and managing them in groups. Develop your own applications over the air and roll them out on your IoT devices worldwide.

Data science made simple

Import data from a variety of sources to transform and create data models. Generate instant reports and visualize your data in custom infographics.

Knowledge

From the Record Evolution blog

The IoT Process Flow: Why the Internet of Things Is not a Project

The IoT Process Flow: Why the Internet of Things Is not a Project

IoT implementation is a highly complex, costly, and time-consuming effort. So why should it make sense for so many companies to throw themselves into the uncertain journey of implementing on-premises

Cloud Computing for Sustainable SMEs

Cloud Computing for Sustainable SMEs

Providing a competitive advantage against corporations, sustainable cloud computing solutions have been named the ultimate equalizer for small and mid-sized companies and a decisive step toward digital maturity.

Data Security in the Cloud: Key Concepts and Challenges

Data Security in the Cloud: Key Concepts and Challenges

Back in 2017, the cloud was declared to be “the new normal”. A survey revealed that 83% of enterprise workloads are expected to run from the cloud by 2020. This

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