Novo 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.
Overview
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.
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Inspect the highlighted sourceThe challenge
Employees across Novo Nordisk had ideas for solving their own business problems with generative AI, but were limited because they could not develop the applications or maintain the infrastructure to support them; the company also found it difficult to predict which use cases would take off and which would be less valuable, while needing innovation to remain secure, compliant, and cost-effective.
The solution
Novo Nordisk built a self-service generative AI platform on AWS, centered on Amazon Bedrock, that lets employees build and customize chatbots and agents for use cases across nonregulated business processes. AWS Partner Cloud2 Oy (formerly KeyCore) validated the architectural design to keep the solution secure and scalable, and the platform runs on serverless AWS services, including Amazon DynamoDB and AWS Lambda, to keep base costs low.
Reported business value
More than 25,000 Novo Nordisk employees have used the platform to create chatbots for over 2,500 use cases, bringing the cycle of building a chatbot down from months to days (or about one hour for a proof of concept), at an average cost of around $10 per use case per month. More than 1,000 employees use the company's general-purpose, off-the-shelf chatbot, which processes over 26,000 prompts a month, and the largest use case was trained on 140,000 documents.
Sources
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Novo 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 DynamoDBNovo 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 Studio
Roche launches NVIDIA AI factory to accelerate the development of new therapeutics and diagnostics solutions
Roche deployed 2,176 NVIDIA Blackwell GPUs on premises across the United States and Europe, bringing its combined on-premise and cloud GPU infrastructure to more than 3,500 Blackwell GPUs. The AI factory is embedded across the value chain: NVIDIA BioNeMo powers Roche's Lab-in-the-Loop strategy connecting biological and chemistry experiments with AI models in R&D; NVIDIA Omniverse-powered digital twins optimize manufacturing production lines and factory designs; accelerated computing and NVIDIA Parabricks analyze diagnostics datasets and digital pathology images; and NVIDIA NeMo Guardrails support healthcare-grade conversational AI in digital health. The expansion builds on a NVIDIA collaboration that started in 2023, and Roche's U.S. subsidiary Genentech also leverages the infrastructure for drug discovery.
Roche· SwitzerlandNVIDIA Blackwell · NVIDIA BioNeMo · NVIDIA Omniverse +2
Using Amazon Bedrock Agents to Accelerate Decisions Across Drug Development at AstraZeneca
AstraZeneca built Development Assistant, a multi-agent AI tool using Amazon Bedrock Agents, that lets clinical, regulatory, safety and quality teams ask natural language questions and get insights from structured and unstructured data in seconds via text-to-SQL generation and retrieval-augmented generation. A supervisor agent routes queries to specialized subagents (terminology, clinical, regulatory, database). Built on AstraZeneca's Drug Development Data Platform (3DP), the tool moved from concept to production in 6 months, including cybersecurity and AI governance checks, and is scaling to over 1,000 users.
AstraZenecaAmazon Bedrock Agents · Amazon Bedrock · Text-to-SQLWas this helpful?
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