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Wholesale and retail

Data-empowered digital commerce

To stand out in the global competition, wholesale and retail companies need to tap into process and customer data and think about the value they can extract from analytics. 

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Manufacturing industries

Customer-centric, data-led manufacturing

For manufacturers, true digital transformation starts by envisioning where in the value chain can data be applied to make a difference.

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Public Sector

Accessible and intuitive public services

All public sector services should be designed to serve citizens first. Digital solutions and applications must be easy to use, despite physical and cognitive disabilities.

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Energy and utilities

Dynamic and resilient energy economy

Digital processes and data-led services help energy and utility sector companies develop a stable energy offering with transparent, customer-centric services.

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Digital platform economy

Fast-tracking innovative business models

Shared platforms offer fast entry to new markets, cost-efficiently and scalably. But lasting value add comes from cross-industry collaboration and linking products with complimentary services.

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Banking, finance and insurance

Agile business, customer-centric services

Digitally disrupted, the companies in the banking, finance and insurance sector must actively innovate new approaches to build omnichannel customer experiences that fully utilize data.

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Medical devices manufacturers

User-centric healthcare applications

While medical device software is strictly regulated, there's room for innovations that make life easier for patients and caregivers. Stable and secure data flow is a must.

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Case Altia: Ensuring product quality through machine learning for Altia


Altia wanted to improve quality assurance by automating the fault detection further, thus giving the quality assurance team the possibility to focus on more challenging tasks. With raised accuracy, waste would also be reduced, as the production line can be stopped and fixed if errors occur.

Image recognition to the rescue

We wanted to investigate if machine learning could produce a more accurate result than the human inspector. A cloud-based and on-premise solution were both used in order to test accuracy, and over 1200 images were used as a training set for the AI. The end results: near 100 % accuracy in recognition in both the cloud and on-premise solutions. Altia now has the capability to divert quality inspection resources to more complex matters. We are currently implementing the solution at the Rajamäki factory.

We helped the customer:

  • Scope the problem for proof of concept

  • Create the data set to test drive the algorithms

  • Train their people in machine learning problem solving

  • Build the prototype into the cloud and on-premise for comparison purposes

  • Create the business decision materials and justifications for the actual project

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