Customer cases

Our employees and customers are our most important resource, which is why we are so interested in how you value our work.

Case – Semler Gruppen

Case – Semler Gruppen

A consultant from Specialisterne helps the car import company Semler Gruppen with completing automated tests that are a part of maintaining systems regarding the communication with dealers and workshops. These systems are crucial for the company’s business.

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Case – SDC

Case – SDC

A consultant from Specialisterne assists the financial IT-company SDC in testing new and existing software solutions for banks in Denmark and the rest of the Nordic countries.

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Case – Novo Nordisk

Case – Novo Nordisk

Through planning and facilitating a recruitment process, Specialisterne have helped Novo Nordisk to recruit four new employees with autism in positions where the candidate’s special skills can create value.

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Case – Nordea

Case – Nordea

Specialisterne has facilitated a recruitment process which helped the bank Nordea find seven new IT-workers with an autism spectrum disorder for the bank’s automation-team.

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Case – YouSee

Case – YouSee

Since 2008, consultants from Specialisterne havebeen in charge of testing smartphones, apps andservices for YouSee Mobile before the products getreleased to customers.

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Case – IHFood

Case – IHFood

A group of consultants from Specialisterne scanned, analyzed and classified 30.000 images a month to train the expert systems in IHFood’s intelligent solutions for the food industry.

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Case – Copenhagen Municipality

Case – Copenhagen Municipality

Over a period of five years, Specialisterne has worked with Copenhagen Municipality to quality assure the parking counts; which are a part of every political decision regarding new construction projects in the capital area.

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Case – THE DANISH INSTITUTE FOR HUMAN RIGHTS

Case – THE DANISH INSTITUTE FOR HUMAN RIGHTS

With the usage of text mining and machine learning, Specialisterne has helped The Danish Institute for Human Rights develop a database, which shows how initiatives in the area of human rights are linked to UN’s Sustainable Development Goals.

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Case – LEO Pharma

Case – LEO Pharma

The consultants from Specialisterne makes sure that input, cleanup, checking and updating of employee data in LEO Pharma’s global SAP-system happens fast and uniformly.

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Case – Danske Bank

Case – Danske Bank

A consultant from Specialisterne helps Danske Bank’s central finance section with code optimization, streamlining and automation of reporting and software tools.

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Case – Augustinus Fonden

Case – Augustinus Fonden

Specialisterne helped Augustinus Fonden with sorting and cleaning up data collected since 1982, so the registration meets the requirements of GDPR.

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Case – Cowi

Case – Cowi

Specialisterne helped COWI with the challenge of global warming by crushing large datasets and finding significant patterns and figures for the project

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Case – MovieStarPlanet

Case – MovieStarPlanet

Specialisterne helped MovieStarPlanet review and structure the 3D-files behind the game BlockStarPlanet, as it needed to be migrated to a new platform.

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Case – Copenhagen Airports

Case – Copenhagen Airports

Specialisterne has helped Copenhagen Airports with recruiting three autistic employees for screening of checked-in luggage in Security. The three new employees bring to the job, amongst other skills, pattern recognition and an extraordinary ability to focus.

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Case – TimeLog

Case – TimeLog

A team of consultants from Specialisterne helped TimeLog over the course of several months with manual testing and validation of thousands of data, because a big customer had to upgrade to TimeLog’s new version.

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Case – SimCorp

Case – SimCorp

Consultants from Specialisterne help the publicly listed Danish company SimCorp in the process of migrating the company’s IT infrastructure and services from local data centers to a cloud-based solution

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Case – PwC

Case – PwC

A consultant from Specialisterne has, with their flair for pattern recognition in unstructured data, helped the accounting company PwC with manually cleaning and streamlining data from their customer’s financial systems faster and with fewer mistakes.

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