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Our skills

From embedded software to cloud, data analytics and AI-driven insights

Our expertise is primarily centered on the design and development of software, leveraging cutting-edge tools, languages, and frameworks to deliver highly efficient and scalable solutions.

We specialize in embedded software development, cloud management and development, and data analysis. This allows us to provide tailored solutions for a wide range of industries and applications, spanning from automotive to industrial sectors.

Lastly, we apply our skills in machine learning and artificial intelligence to deliver innovative solutions, such as predictive analytics, enabling our clients to achieve significant competitiveness in their respective fields.

Embedded software

We leverage Linux on ARM platforms, integrating the most advanced and efficient technologies with modern programming languages such as C++ and Rust, to ensure optimal performance and maximum flexibility.

To guarantee interoperability and seamless integration with other systems, we use standard automotive and industrial protocols such as CAN/J1939 and Modbus.
We provide REST APIs and use protocols like MQTT and Kafka, enabling advanced IoT communication with efficient and reliable connectivity between devices and the cloud.

We enforce robust security measures, such as hardening embedded devices, utilizing strong protocols for device authentication and authorization, and encrypting data at its origin.
Secure Elements are employed to protect sensitive data, while anti-tampering mechanisms, secure boot solutions, and rigorous code integrity checks ensure the reliability of our software and firmware.

We utilize Docker and Podman for containerization, enabling scalable and efficient application deployment. In specific scenarios, we also employ hypervisors and virtual machines to create isolated, secure environments, further enhancing the flexibility and robustness of our systems.

Cloud computing

We specialize in delivering both cloud and on-premises solutions, with expertise in AWS and Azure for cloud deployments. We build scalable applications using Kubernetes for container orchestration and design efficient serverless architectures.

We implement reliable CI/CD pipelines for continuous integration and delivery, ensuring fast and consistent deployment cycles. Additionally, we use Infrastructure as Code (IaC) with Terraform to automate resource management across both cloud and on-premise environments.

Our team is proficient in a variety of programming languages such as Go, Node.js, C#, .NET, Java and Python, providing flexibility to meet the needs of each project.

We design and optimize data warehouses for advanced analytics and handle parallel computation for high-performance workloads.

Finally, we create intuitive and responsive user interfaces with React and Angular, prioritizing exceptional UI/UX design to ensure a seamless user experience.

Data analytics and Machine learning

We use advanced technologies to analyze large amounts of data from various sources. Our process includes data ingestion and ETL (Extract, Transform, Load) to clean, organize, and prepare data for analysis. In machine learning and AI, we develop and manage datasets for training models, including images, text, and other data types.

These datasets are used to train models with frameworks like PyTorch or TensorFlow to deliver insights and accurate predictions. Models can be accessed via REST APIs or deployed on edge devices. We use tools like MLOps and MLflow to efficiently manage the entire model lifecycle, from development to deployment and ongoing monitoring.

We also use collaborative systems like Jupyter, Colab and Databricks for shared workflows, enabling teams to work together on data analysis and model development. For large-scale data processing, we leverage parallel computation frameworks like Apache Spark.

For industries like automotive, we create solutions for anomaly detection and predictive maintenance, assess driver behavior to identify risks and inefficiencies, and offer suggestions to improve safety and efficiency. We also monitor complex systems, predicting failures by comparing real-time data with their Digital Twin.