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Large companies are increasingly looking for ways to move from selling physical products to selling the functionality of these products as a service. Rolls Royce, for example, a leading manufacturer of jet engines alongside luxury cars, now allows airlines to subscribe to a engine as a service offer per kilometre. Companies pay based on flight hours and the type of trip. This helps airlines control costs and puts pressure on Rolls Royce to improve quality and reduce maintenance costs.
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 scale their data infrastructure to share operational data that enables product-as-a-service offerings between partners.
Trusted twins, based in Gdansk, Poland, has raised $1 million in pre-seed funding to meet this challenge. The platform uses digital twins of real and abstract objects to communicate between 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 co-founder, Krzysztof Malicki, told VentureBeat that he started working on the company in 2020 when he suspected that companies would soon be collaborating around digital ledgers representing objects. “The digital twin philosophy is perfect for operational data sharing in real time,” he said.
Many low-code tools for developing applications exist within the business. But there are fewer options when companies try to share operational data across corporate boundaries.
“Today, if you want to share operational data with partners, you really have to develop a solution yourself,” says Malicki.
A utility meter company turned to Trusted Twin to move from selling meters to providing metering as a service to utility companies. Trusted Twin automates governance to share data with customers in a secure 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 happened. Trusted Twin, on the other hand, focuses on operational data that provides real-time information about processes, services, objects and settings that are live.
“There just aren’t many options on the market right now for B2B sharing of operational data,” says Malicki.
Trusted Twin’s platform promises to complement existing data analytics platforms. For example, in a predictive maintenance application, analytical data stored in data lakes can help train data models to identify failure patterns. Trusted Twin helps create apps that correlate live data with these failure patterns. Then the app can automatically schedule a third-party maintenance company to replace critical parts when a breakdown is imminent.
Adapt to different data structures and types
Trusted Twin took an object-oriented approach to storing and sharing data. Teams create digital twins to display objects with an open and dynamic structure. This allows teams to model real or abstract entities.
A 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 shape in response to new projects.
Another big challenge was supporting wildly different data types. Trusted Twin has developed tools for ingesting data from various sources such as JSON, media files, documents and time series data.
The platform also helps onboarding data with different structures and mixed data types from different partners. At the same time, it enforces ownership and control from each partner.
Later, decentralized data structures could make it easier for companies selling physical products to move to product-as-a-service models. Decentralized data platforms help reduce data governance and integration issues around collecting live data from customers. This data can help engineers identify opportunities to improve equipment efficiency and reliability.
Trusted Twin financiers include ff Venture Capital, Presto Ventures, Movens Capital, RKKVC, Startup Wise Guys and several leading 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 deployments.
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