Software Development

In 2021, Semcon acquired Swedish IT companies Squeed and Tedsys, thereby reinforcing its digital expertise with heightened excellence and breadth in software and system development.

"We have noticed that many companies have interconnected their products and are now ready to take the next step. They may need help with product improvement, building new cloud solutions, or identifying solutions that support servitisation. We derive most satisfaction from the opportunity to support our customers in the creation of new business models through smart data use."

- Per Hagman, Head of Software Excellence

Learn more about Squeed.
Learn more about TedSys.

To deliver optimal solutions to our customers, we need a high-performance organisation using quality-assured and efficient tools and processes. But most important of all - we need motivated and talented employees. We have chosen to call this Software Excellence - something we at Semcon see as a promise to both our customers and our employees:

• A promise to our customers, which means that Semcon will always be a high-performance organisation that delivers quality-assured solutions, takes responsibility for maintaining the solutions, and gives continuous updates on the latest technology trends.

• A promise to our employees, which means that we prioritise the competence of the individual by building a competence-driven culture based on continuous learning from each other and from the outside world. This is driven forward by our "Community-of-Practice" (CoP), among other things, where our subject matter experts gather to share competence and tackle challenging problems.

Selection of Semcon's expertise in software

We have a broad competence in software development but would like to highlight certain areas in particular, areas where we have a significant edge:

Embedded: We have a long history of developing embedded software for a wide range of products, such as medical equipment, measuring systems, smart chargers, cars, bank login devices, and many other gadgets.

We use the latest frameworks in real-time systems and Embedded Linux. Together with modern sensor technology, this allows us to build customised Linux distributions using Yocto. We build embedded products that call for both long battery life and stable connection. The most common programming languages we use are C, C++, Python, Java and Bash.

IoT: Starting from products with embedded software, the next step is often to interconnect them in order to create increased opportunities for the end user. Either directly with other products, peer-to-peer, in a common mesh network, or with a cloud platform. This is achieved through 4G, 5G, LTE, Bluetooth, BLE, Zigbee/Matter, Lora, Narrow Band, Ultra Wide Band, etc., based on the need.

Interconnection can be very demanding, depending on the requirements and location of the product. The product may be located deep in the forest, down a mine, or submerged in water. There may also sometimes be strict requirements for long battery life, or a great need to transfer large amounts of data to the surrounding systems.

Cloud: We are an independent provider with good proficiency in the major cloud providers (CSP) such as Amazon AWS, Microsoft Azure, and Google GCP. We usually work with two approaches in the cloud. We either connect an existing product to a cloud platform, where we create services that add value for the end user. Or we create a pure cloud product (cloud-native) that focuses on e-commerce, streaming, financial technology, or retail, for example.

Our focus in cloud services consists of cloud architecture and software development in Java, C# and Golang.

Data Science: Thanks to long experience in product development combined with our understanding of the end user, we can help our customers to build new services and solutions based on the data generated by IoT and Cloud solutions. Here we work with the latest technologies in machine learning, statistical analysis, and data engineering.

The focus within machine learning is on reinforcement learning, federated learning, semantic segmentation, object detection, ML verification and validation, and natural language processing. Common tools, toolboxes and languages used in data science include Python, Tensorflow/Pytorch, Google Colab, SpaCy, CoreNLP, NLTK, Pandas, NumPy, SciPy and Scikit Learn.