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Large enterprises are increasingly looking for ways to transition from selling physical products to selling the functionality of these products as a service. For example, Rolls Royce, which is a leading maker of jet engines in addition to luxury cars, now allows airlines to subscribe to an engine-as-a-service offering by the mile. Companies pay based on hours in flight and the type of trip. This helps airlines control costs and puts the burden on Rolls Royce to improve quality and lower the cost of maintenance.
It’s one thing for a $6 billion company like Rolls Royce to do the programming and integration to turn products into services. However, smaller enterprises may struggle to to scale up their data infrastructure to share operational data that powers product-as-a-service offerings across partners.
Trusted Twin, based in Gdansk, Poland, has raised $1 million in pre-seed funding to address this challenge. The platform uses digital twins of real and abstract objects to communicate across business teams, developers and data scientists from different companies.
This promises to streamline the development of new applications that take advantage of operational data from many sources, including facilities, equipment and business applications. These applications can improve predictive maintenance, logistics and order-fulfillment business processes.
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Digital twins for data sharing
Trusted Twin CEO and cofounder, Krzysztof Malicki, told VentureBeat he started to work on the company in 2020 when he had a hunch that companies would soon be collaborating around digital ledgers representing objects. “The digital twin philosophy is perfect for operational real-time data sharing,” he said.
Many low-code tools exist for developing applications within a company’s operations. But there are fewer options when companies try to share operational data across company boundaries.
“Today, if you want to share operational data with partners, you basically have to develop a solution of your own,” Malicki said.
One company that makes utility meters turned to Trusted Twin to shift from selling meters to providing measurement as a service to utility companies. Trusted Twin automates the governance to share data with customers in a safe and controlled manner. It also streamlines integration in the cloud. This allows the company to focus on developing a better meter and on business development rather than application integration.
There are also plenty of data analytics tools like Snowflake and data lakes for analyzing data about things that have happened. In contrast, Trusted Twin focuses on operational data that provides real-time information about processes, services, objects and settings that are live.
“There simply aren’t many options right now on the market for B2B sharing of operational data,” Malicki said.
Trusted Twin’s platform promises to complement existing data analytics platforms. For example, in a predictive maintenance application, analytics data stored in data lakes could help train data models to identify failure patterns. Trusted Twin helps create apps that correlate live data with these failure patterns. Then the app could automatically schedule a third-party maintenance company to replace critical parts when a failure seems imminent.
Adapting to different data structures and types
Trusted Twin adopted an object-oriented approach to storing and sharing data. Teams create digital twins to represent objects with an open and dynamic structure. This allows teams to model real or abstract entities.
One big challenge they are working on is making it easier to support objects with dynamically changing structures. This could be a warehouse that changes layout, a factory that is reconfigured for new products, or a business process that changes form in response to new projects.
Another big challenge was to support wildly different data types. Trusted Twin has developed tools for ingesting data from sources as diverse as JSON, media files, documents and time-series data.
The platform also helps onboard data of different structures and mixed data types from across partners. At the same time, it enforces ownership and control by each partner.
Down the road, decentralized data structures could make it easier for companies that sell physical products to transition to product-as-a-service models. Decentralized data platforms will help mitigate data governance and integration concerns around collecting live data from customers. This data can help engineers identify opportunities to improve the efficiency and reliability of equipment.
Trusted Twin backers include ff Venture Capital, Presto Ventures, Movens Capital, RKKVC, Startup Wise Guys and several high-profile angel investors. The company has raised $1 million in funding to date. Malicki said they plan to use the money to improve customer development and refine the product for large-scale implementations.