Hyperscience Acquires Boxplot To Deliver Data Processing And Graph-Based Data Storage In One Platform

Marking the machine learning company’s first acquisition, Hyperscience is now positioned to significantly accelerate product innovation to deliver better, faster, and more accurate outcomes to customers

Hyperscience, the human centered automation company,  announced it has completed the acquisition of Boxplot, a startup based in Berlin, Germany. Boxplot provides a graph data modeling tool that enables organizations to visualize and better understand their customers’ data and explore how it relates to other data across their organization.

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Boxplot reinforces Hyperscience’s core proposition of transforming human-readable data into machine-readable data, critical to solving today’s customer management challenges. End-customers are often impacted by slow processes, such as several weeks instead of days to process a mortgage or a medical insurance claim.

The Hyperscience Platform enables organizations to take unstructured data that arrives in various different formats – such as policies, invoices and emails – and read and understand them at scale, which speeds up processing times tenfold. The combination of the Hyperscience Platform with Boxplot’s graph technology will result in faster and better decisions, such as how to price insurance, who to give a mortgage to, which invoices to pay out, and detecting where fraud exists. This elevates and improves the customer experience and organizational agility.

The deal was signed on December 6, and marks Hyperscience’s first acquisition.

Delivering Better Outcomes to Customers

Organizing data into customer-defined graphs (i.e. networks of information, where each piece of data is linked by a relationship to other pieces of data) is also important when an organization wants to deploy multiple business processes, as this data will often be shared. For example, when processing an insurance claim, it’s important to retrieve the claimant’s policy. That claim needs to be linked to a person, who is in turn linked to a policy.

Many customers currently perform that lookup manually by diving in and out of different systems of record. Boxplot will provide the backplane for business process interoperability, while simultaneously making Hyperscience a system of record that delivers a cross-organizational view of data. This will enable more automation and better machine learning performance.

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Shared Vision for a Future of Human Centered Automation

Peter Brodsky, CEO and co-founder of Hyperscience, said: “At Hyperscience, we believe that machines and people work better alongside one another. This is a core tenet of what we call human centered automation.” He added: “Hyperscience processes data and Boxplot connects and stores data relationships. The two fit together harmoniously because how data is stored determines how it can be processed, and vice versa. Importantly, Boxplot fits into our vision for how automation will play out in the future. This acquisition represents an important step forward for us and for the market. The team coming on board will fit well into Hyperscience, and continue to drive us forward to our human centered automation vision.”

Fabian Schmidt-Jakobi, CEO and co-founder of Boxplot, added: “Hyperscience and Boxplot complement each other’s technological innovations and like-minded vision for organizations of the future. Their market-leading automation and machine learning capabilities for data structuring combined with our graph-based enterprise operating system will be a powerful combination. We’re looking forward to joining the Hyperscience team, and to working together to achieve more for our current customers and expand to others globally.”

Neil Ward-Dutton, vice president, AI, Automation and Analytics Europe at IDC, said: “As vendors of automation and intelligence technologies mature and start to address implementations at scale, they invariably find that solving integration and data management challenges are big contributors to the overall effort of delivering on customers’ objectives. Being able to simplify the business of managing business process data, and sharing that data across business processes, is a critical strategic enabler for any vendor that wants to support multiple automation use cases for customers – and do it well.”

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