Databricks
7 use cases using this technology
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.
Maya is simplifying banking for diverse populations
Maya
Maya, the Philippines' leading fintech company, partnered with Databricks to modernize its data architecture into a unified lakehouse on Delta Lake, centralizing 100% of its data for real-time access and AI scalability. Maya's ML-powered underwriting tools cumulatively disbursed $2.1 billion in loans by year-end 2024. AI-driven fraud detection, combining transactional sequence embedding, network analysis and predictive modeling, achieved up to a 98% reduction in fraud losses. Hyperpersonalized, AI-driven marketing campaigns increased average revenue per user (ARPU) by 45%. Using Unity Catalog for governance and automated ETL pipelines, Maya also achieved a 28% increase in storage capacity without a rise in costs.
AkzoNobel builds portfolio of 60+ autonomous AI agents on RISE with SAP and Databricks foundation
AkzoNobel
AkzoNobel consolidated 46 ERP systems down to a planned 4, standardizing on RISE with SAP and harmonizing master data with Deloitte, then connected the SAP environment to Databricks to combine structured and unstructured data for AI. On this foundation, AkzoNobel's IT organization built a portfolio of more than 60 AI agents that autonomously execute tasks such as releasing credit blocks and handling HR and logistics transactions, fully autonomously carrying out more than 750,000 actions in the first nine months, with 90% of credit blocks now resolved automatically.
Michelin runs 200+ AI use cases across manufacturing, supply chain and innovation
Michelin
French tire manufacturer Michelin has more than 200 AI use cases in production, led by group chief data and AI officer Ambica Rajagopal. Its in-house IRIS system, protected by over 20 patents, partially automates end-of-line visual tire defect inspection to improve inspector efficiency and workplace ergonomics while operators retain final accountability. Machine learning forecasting tools improve demand forecast accuracy and proactively detect stock shortages in the supply chain. Michelin scans the startup ecosystem and uses tools including Databricks and Dataiku, and has partnerships with Microsoft and Rockwell Automation to codevelop AI solutions. The company reports AI-project ROI exceeding €50 million per year, growing 30-40% annually for three consecutive years, governed by an internal data office and responsible-AI principles (people-centric, explainable, accountable).
How 7-Eleven, Inc. Built a Game-Changing GenAI Creative Assistant for Marketing with Databricks
7-Eleven, Inc.
7-Eleven's AI Center of Excellence built a multi-agent GenAI marketing assistant using LangGraph and Databricks, moving beyond early document-based chatbots and basic RAG. The system includes a Campaign Creative Generator, Copywriter Bot, General Assistant, and Supervisor Agent that orchestrates workflow and reviews outputs, with human-in-the-loop review, web search for trend intelligence, and guardrails filtering toxicity, PII and off-policy responses. Databricks provides governance and observability via MLflow tracking, automated agent evaluation, and inference tables. The assistant reduced manual creative hours, with campaign concepting and scripting that used to take hours or days now generated, refined, and approved in minutes; user feedback included calling it 'a game changer' and 'better than ChatGPT.'
Lippert Improves Customer Support with GenAI
Lippert
Lippert, a $3.8 billion global manufacturer of components for RV, marine and automotive brands, used Databricks and Agent Bricks to consolidate fragmented data into a single lakehouse and deploy AI agents for customer support. An AI assistant trained on product manuals, technical case history and field-expert videos surfaces troubleshooting guidance for call center agents in real time, cutting new-agent ramp time from six months to four weeks (an 85% reduction). Using Agent Bricks' evaluation framework and synthetic data, model accuracy for the support agent improved from 33% to 84% within weeks. AI also analyzes thousands of support calls daily for coaching and quality scoring (versus a prior manual sample of 100 calls/month) and automates call summarization into Salesforce. The initiative is expected to save millions per year and reclaim hundreds of thousands of hours, with new agents planned for HR, warranty and supply chain.
Novartis: Accelerating Drug Development with AI-Powered Clinical Trial Transformation
Novartis
Novartis partnered with AWS Professional Services and Accenture to modernize their drug development infrastructure and integrate AI across clinical trials, with the goal of reducing trial development cycles by at least six months. The initiative built a GXP-compliant data mesh platform on AWS with Databricks for processing, enabling AI use cases including protocol generation and an intelligent decision system (digital twin). Early results from the patient safety domain showed 72% query speed improvements, 60% storage cost reduction, and 160+ hours of manual work eliminated. The protocol generation use case achieved 83-87% acceleration in producing compliant protocols.