GrabIT

Working with our awesome friends at 3fs, our full-stack engineers developed MDI - a cutting-edge platform addressing the need for robust multi-level authentication and authorization. Utilizing SIM cards as secure digital identities, MDI ensures heightened security for accessing applications. The PHP-based API orchestrates authentication, while a Go-based API manages database interactions with Cassandra. The User Management Portal and Admin Application enhance user control, customization, and administrative functions. MDI offers a simple yet secure solution, allowing users to choose authentication methods like SMS codes or mobile applications. The platform pioneers innovative cybersecurity, leveraging SIM card identities for enhanced digital security.

Tasked with optimizing the performance of low-power robots in human environments, our team developed the Kolektor platform, leveraging Go and ROS. Key features include custom log collection, real-time monitoring, and integration with ROS for data exchange. Additionally, the platform offers webcam feed integration, enhancing remote operators' situational awareness. The result? Kolektor revolutionized robot monitoring, enabling swift issue detection and resolution, thus boosting operational efficiency and reinforcing our commitment to robotics innovation.

The case study outlines the development of a live streaming app for content creators by iVentureGroup, utilizing Next.js, GraphQL, and Tailwind CSS. Features include seamless integration with external services, user engagement tools like live streaming and real-time chat, and an emphasis on SEO optimization and modern design. The resulting application surpassed expectations, offering content creators a powerful platform for engagement and management.

Aviat, one of our long-term clients, faced challenges in efficiently developing and executing tests across their diverse product portfolio. Traditional test automation methods require extensive programming knowledge, limiting the involvement of non-technical people. To address this, the company embarked on creating a QA Framework for their internal use - a comprehensive solution that simplified test case automation and empowered testers without deep programming expertise. The primary goal of the framework was to streamline the process of test case development and execution across multiple products while minimizing the need for programming skills. The framework aimed to provide a user-friendly environment where testers could efficiently create, manage, preview, and execute preconfigured tests, with the use of an intuitive user interface.

iVentureGroup, a leading Berlin-based company, embarked on a mission to construct a highly sophisticated marketing machine within the realm of online entertainment. The ambitious goal was to optimize campaign management, enhance banner and landing page delivery, streamline partner integrations, and generate comprehensive, customized reports based on registrations. To achieve this vision, iVentureGroup entrusted GrabIT to take over the project in 2019. Armed with a diverse set of cutting-edge technologies, GrabIT began the journey of transforming the Digital Performance platform into a robust, efficient, and dynamic marketing engine.

Triglav, an insurance company, sought to automate the identification of misrepresented policy renewals using Machine Learning (ML). The solution, developed on IBM Cloud and Watson, involves feature creation, an ML model for policy pair comparisons, and a rule-based system for accuracy. Migrated to a new environment and updated, the automated pipeline accelerates the identification of potentially misrepresented policies, improving efficiency and facilitating human validation where needed.

For Telenet Belgium, we tackled the challenge of determining the optimal price increase for telecommunications services. Faced with the delicate balance between maximizing revenue and minimizing customer churn, we employed a comprehensive approach. By modeling the impact on various factors, including ARPU, churn, and gross adds, we identified a bell-shaped revenue curve. This curve pinpointed the optimal price increase, providing valuable insights for the client on high-risk groups and more.

ING Bank partnered with a team comprising a senior data scientist, data scientist, and project manager to address operational and legal/regulatory risks crucial to their operations. Leveraging SAS Viya, they developed a robust tool for real-time risk monitoring and scoring, focusing on non-financial risks. The solution includes a comprehensive pipeline for data analysis, scoring, and scenario simulations, enabling proactive risk management, informed decision-making, and resource allocation. By enhancing compliance and reducing operational disruptions, the system contributes to cost reduction and organizational resilience.

Blue Ocean Gaming engaged one of our Senior Data Scientists, to boost user engagement through personalized game recommendations. Using advanced algorithms, they developed a two-phase system: fast retrieval and ranking. This dynamic approach significantly improved user satisfaction and game relevance.

The project addressed both regulatory and BI reporting needs. For regulatory reporting, manual processes were replaced with an automated ETL job using SAS Enterprise Guide and Python scripts, streamlining data collection, preprocessing, and output preparation for the performance management system Tagetik. BI reporting involved creating interactive dashboards with SAS Visual Analytics, later migrated to SAS Viya, ensuring granular access rights for bank employees. The outcome was significant time savings through automation and improved accuracy, facilitating efficient reporting and data analysis for internal use.

With the introduction and increased use of digital technologies in the retail industry, retail shops experience massive volumes of data. The data stores use consists of information on customer demographics, transactional data, sales quantity, geographical data, coupon and discount usage, registry telemetry, supply chain logistics, and more. This provides retailers with an opportunity to gain insights into customer preferences, trends, shopping behaviors, pricing adjustments, inventory management, and other advantages, and holds great potential for the businesses to improve or optimize processes, increase sales, enhance customer experience, and other desired strategies. The goal was to use Machine Learning and advanced analytics to identify important segments and cohorts of customers, predict customer churn, calculate the quality of items, analyze telemetry, and optimize the distribution logistics of item delivery to the stores. This resulted in conducting several analyses, creating a knowledge graph database, building several Machine Learning models, putting them in production, and creating multiple dashboards and visualizations.

GrabIT, in collaboration with our partner 3FS, played a pivotal role in the successful implementation of the IoT Accelerator Cloud Connect project. This groundbreaking solution simplifies secure connections between low-power cellular devices and popular public cloud IoT endpoints, such as AWS IoT Core, Azure IoT Hub, and Azure IoT Central. By leveraging advanced technologies and expertise in Go, Angular, MySQL, PostgreSQL, GitLab CI/CD, Docker, Kubernetes, Helm, Ansible, AWS, Prometheus, and Grafana, our team delivered exceptional results that revolutionized the IoT landscape. For more information on this case study and several others, please visit our website at https://www.grabit.io/industry-expertise.