AI use cases in Denmark
11 documented implementations
Danfoss and Go Autonomous Automate B2B Email Order Processing on Google Cloud
Danish manufacturer Danfoss partnered with Go Autonomous to implement its Autonomous Commerce platform, hosted on Google Kubernetes Engine, which uses specialized AI models and AI agents to interpret and execute B2B customer requests from incoming emails and attachments by triggering the appropriate actions in Danfoss's ERP software. Danfoss reports automating up to 80% of transactional decision-making and communication, reducing processing time by 50%, and consolidating a workflow spanning up to five systems into a single interface; it is live in over 20 countries.
Danfoss· DenmarkGoogle Kubernetes EngineSaxo Bank Developers Use GitHub Copilot in Almost Every New Application
Danish broker Saxo Bank rolled out GitHub Copilot to more than 400 of its 700+ platform developers, who now use it to generate code, debug errors and write test code in almost all new application development, with an overall code-acceptance rate of around 30%. Saxo also built a client-facing chatbot on Azure OpenAI with controlled responses limited to approved help content, and sent engineers to Microsoft's AI Co-Innovation Lab in Munich to prototype a news recommendation engine using large language models.
Saxo Bank· DenmarkGitHub Copilot · Azure OpenAI · Microsoft 365 Copilot +1
Pandora Builds AI Shopping Agent Gemma and Service Agent Clara with Agentforce
Jewelry brand Pandora built two Agentforce AI agents: Gemma, a personal shopper that reasons across Commerce Cloud order history, Bloomreach recommendation data and Databricks insights via Data 360 to make tailored jewelry recommendations in a warm, in-store-like tone, and Clara, a customer service agent built with Salesforce Professional Services and Publicis Sapient that answers "Where is my order?" requests and FAQs, deflecting 60% of cases.
Carlsberg builds AI knowledge base in two days with Microsoft Unified
Carlsberg Group built Global Brain, a large language model knowledge assistant on Azure OpenAI Service and Copilot Studio, developed in two days, that reduces time to query 4,000 operational supply chain standards by about 99% for over 10,000 supply chain workers, cutting 30-minute manual searches down to seconds.
Carlsberg Group· DenmarkAzure OpenAI in Foundry Models · Microsoft Copilot Studio · Microsoft Power Platform +2Novo Nordisk uses machine learning and computer vision to automate pharmaceutical manufacturing quality checks
Novo Nordisk, a Danish pharmaceutical company that supplies nearly 50 percent of the world's insulin, built an automated ML pipeline on AWS using Amazon SageMaker Pipelines to train, deploy, and monitor computer vision models on edge devices. The system automates previously manual tasks including counting drug cartridges in boxes and detecting bacterial anomalies on agar plates, using a robotic arm, camera rig, and edge inference, with results monitored via an Amazon QuickSight dashboard. The solution deploys ML models at scale to different edge devices, automates quality-assurance tasks, improves time to market, and was successfully repurposed from the cartridge-counting use case to the agar-plate anomaly detection use case with minimal changes.
Novo Nordisk Transforms Clinical Trials With Generative AI
Novo Nordisk, a Denmark-headquartered global healthcare and pharmaceutical company, used the Databricks Data + AI Platform to unify previously siloed clinical trial data across its FounData and DataCore platforms. In 9 months it moved from concept to MVP, and now over 20% of its development organization actively uses clinical data via FounData. The company built a 'Co-Scientist' AI agent system on Databricks Agent Bricks, Unity Catalog and AI/BI Genie to search clinical data and surface curated insights, with an expected $157M+ in net new value and $14M in efficiency gains from optimized clinical trials over five years.
Novo Nordisk· DenmarkUnity Catalog · Agent Bricks · AI/BI Genie +2Novo Nordisk Scales to 2,500+ Generative AI Use Cases with Amazon Bedrock
Danish pharmaceutical company Novo Nordisk built a self-service generative AI platform on Amazon Bedrock that lets employees build and customize chatbots for nonregulated business processes. More than 25,000 employees have used the platform to create chatbots for over 2,500 use cases, cutting the time to build a chatbot from months to days, at an average cost of about $10 per use case per month.
Bankdata pilots Microsoft's agentic COBOL Migration Factory against its 70-million-line mainframe estate
Bankdata, a technology company owned by a consortium of Danish banks representing over 30% of the Danish banking market, has over 70 million lines of code still running on the mainframe. Bankdata worked with Microsoft to build the COBOL Agentic Migration Factory (CAMF), a multi-agent system built on Semantic Kernel with specialized agents (COBOLAnalyzerAgent, JavaConverterAgent, DependencyMapperAgent) that analyze, map dependencies for, and convert COBOL programs into modern Java Quarkus applications. Microsoft tested the framework on a small COBOL module donated by Bankdata, progressively validating it on more complex COBOL call chains reaching a call-chain depth of level 3 as the tool matured into its current multi-agent form.
Bankdata· DenmarkMicrosoft Semantic Kernel · GPT-4.1 · AutoGen +1Novo Nordisk accelerates clinical insight with custom agents on Azure
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+.
Novo Nordisk A/S· DenmarkMicrosoft Azure · Microsoft AI Acceleration StudioNovo Nordisk builds AI drug discovery platform on Azure with Microsoft Research
Novo Nordisk partnered with Microsoft Research to build an AI platform on Azure AI and data stacks spanning regulatory affairs, early research, drug discovery and trial design, using Azure OpenAI Service, Azure Cosmos DB and Azure Kubernetes Service, with Power BI and Power Apps for collaboration. The platform includes a copilot for researchers, shared reasoning-chain templates, and governance/auditing of how data and models are used. The teams published early results on predictive AI models for cardiovascular disease risk detection, including an algorithm that Novo Nordisk says predicts patients' cardiovascular risk better than the best clinical standards, drawing on more than 100 years of insulin research data.
Novo Nordisk· DenmarkAzure OpenAI Service · Azure Cosmos DB · Azure Kubernetes Service +2Novo Nordisk Scales to 2,500+ Use Cases with Secure Generative AI Using Amazon Bedrock
Novo Nordisk built a self-service generative AI platform on AWS, using Amazon Bedrock's foundation models, so employees could build and customize chatbots for nonregulated business use cases without needing to develop applications or maintain infrastructure themselves. The company worked with AWS Partner Cloud2 Oy (previously KeyCore) to validate the architecture for security and scalability. More than 25,000 Novo Nordisk employees have used the platform to create chatbots for over 2,500 unique use cases, such as retrieving information, drafting documents, or acting as a virtual colleague or critic. The company's general-purpose chatbot is used by more than 1,000 employees and processes over 26,000 prompts a month; its largest use case was trained on 140,000 documents. Each use case costs around $10 per month to run on AWS, using serverless services including Amazon DynamoDB and AWS Lambda. Building a chatbot now takes days rather than months, and some tasks that took a full day can be completed in as little as 10 minutes.
Novo Nordisk· DenmarkAmazon Bedrock · AWS Lambda · Amazon DynamoDB