Microsoft Azure
10 use cases using this technology
GoJob enhances recruitment capabilities with Mistral
GoJob
Gojob, a French HR-tech platform specializing in temporary worker staffing that processes over 2 million applications and completes approximately 60,000 recruitments annually across Europe and North America, integrated Mistral Large into its recruitment platform on Azure. The GenAI recruiting assistant conducts real-time conversations with candidates to automate pre-qualification and initial candidate screening.
Independer cuts feature delivery 50% with Lakebase
Independer
Independer, the largest independent comparison platform in the Netherlands, used Databricks Lakebase to eliminate the export bottleneck between its Customer 360 data platform (built on Databricks and Unity Catalog) and the production APIs serving its website, customer service tools, and internal analytics. Because customer data had been fragmented across legacy on-premises systems, engineers previously had to write export scripts and load a separate SQL Server instance before building new features. By synchronizing gold tables directly with consuming services via Lakebase (built on PostgreSQL), Independer cut development work for new Customer 360 features by 50% and is now building GenAI agent proof-of-concepts that store state in Lakebase.
Smarter and faster decision-making with all data in one platform
Swedbank
Swedbank, the largest bank in Sweden and third-largest in the Nordic countries with more than 7 million customers, migrated its analytics capabilities and application services to a Databricks-driven platform on Microsoft Azure and implemented Immuta as its unified access control plane. Using a risk-based, twofold sourcing approach that kept on-premises scenarios running in parallel during migration, Swedbank centralized markets and share trading, customer analysis, and cybersecurity data on one internal platform, making AI and machine learning available in one click and enabling shorter development cycles and faster fraud/suspicious-behavior detection.
So nutzt Krones digitale Zwillinge und KI in der Produktion
Krones AG
Krones, working with technology-ecosystem partners Ansys (part of Synopsys), Cadfem, Microsoft Azure, Nvidia (Omniverse/OpenUSD) and SoftServe, developed 'Agentic Digital Twins' that combine physically exact real-time simulation with AI agents capable of judgment and decision-making for beverage production lines. Simulation runs that previously took three to four hours now complete in under five minutes; the AI agents test scenarios and settings, optimize workflows, and transfer the best solutions to real equipment. The digital twin was used in developing Krones' new 'Ingeniq' line concept, presented at Drinktec 2025. Compute-intensive simulations run on Microsoft Azure using Nvidia's accelerated computing platform.
CoreLogic cuts platform costs by 5X
CoreLogic
CoreLogic cut platform costs by 5X after migrating its on-premises RPA platform to Microsoft Power Automate, as part of a Cognizant client engagement.
Novo Nordisk accelerates clinical insight with custom agents on Azure
Novo Nordisk A/S
Novo Nordisk wanted to accelerate pharmaceutical R&D decision-making by helping researchers explore and validate clinical hypotheses faster using AI-assisted quantitative analysis. Working with Microsoft's AI Acceleration Studio (Forward Deployed Engineering team), Novo Nordisk built a governed reasoning agent on Azure, drawing on its FounData initiative which harmonized more than 200,000 patient-years of clinical trial data aligned to CDISC, SDTM, and ADaM industry standards. The agent lets researchers ask complex scientific questions in natural language and generate and execute code against proprietary clinical datasets, with human-in-the-loop validation by biostatisticians before outputs influence decisions. Before production rollout, the teams ran thousands of automated tests and layered evaluation systems. The solution is reducing time to insight from weeks to minutes and increasing the number of scientific questions teams can evaluate from roughly 5-10 strong ideas per quarter to 50+.
Illimity modernizes commercial banking with Databricks and adopts LLMs for customer-centric chatbots
Illimity Bank
Illimity, an Italian digital bank, built its data architecture entirely around the Databricks Data + AI Platform to process data in real time, extract actionable insights and securely share it with partners. Databricks has supported Illimity's adoption of LLMs, using vector embedding and vector databases, to inform its knowledge base and power intelligent customer-centric chatbots. Illimity is also exploring Databricks Clean Rooms to monetize its architecture using deterministic or machine learning models without compromising confidentiality.
AT&T reduces fraud by up to 80% with the Databricks Data + AI Platform
AT&T
AT&T migrated from a legacy on-premises, rules-based fraud detection system to the Databricks Data + AI Platform, moving to a unified lakehouse architecture. AT&T now runs over 100 ML models in production that use real-time data, automatic alerts and recommendations to protect its 182 million wireless customers from fraud including robocalls, robotexts, illegal unlocks and identity theft, reducing fraud by up to 80%.
University of Michigan Offers Several AI Services to Staff and Students
University of Michigan
In August 2023 the University of Michigan launched UM-GPT, becoming (per the source) the first higher education institution to offer AI services at scale, providing secure access to commercially available large language models through the university's private Microsoft Azure environment. Michigan has since launched U-M Maizey, a codeless platform for building custom AI experiences from uploaded data sets using retrieval-augmented generation, with more than 3,500 Maizey instances in production across academic and operational departments, and Go Blue, a mobile AI assistant for campus life. To avoid vendor lock-in, Michigan runs AI workloads across multiple environments including on-premises infrastructure, letting users pick their LLM via a dropdown.
Ørsted uses drones and Cognite Data Fusion for data-driven turbine maintenance
Ørsted
Offshore wind operator Ørsted uses drones to fly inside monopile wind turbines and collect images and sensor data, which is organized in Cognite Data Fusion, powered by Microsoft Azure, to run computer vision models that track corrosion and cracks. The data-driven approach lets Ørsted reduce the number of technicians needed for inspection from four to two and eliminates the need to physically enter confined turbine spaces, improving safety while reducing maintenance cost and downtime.