Databricks powers 7 source-linked AI deployments documented in AIUseCaseHub, across 6 industries and 5 countries. Documented deployments include AI agents, RAG.
7
Use Cases
6
Industries
5
Countries
2
Agent Cases
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Condé Nast migrated 800+ media properties to a unified AWS Cloud infrastructure and built a centralized data platform with Databricks on Amazon S3.The company deployed Amazon Bedrock for content rights management and content moderation, and used Amazon SageMaker for specialized search models.The solution analyzes editorial content together with contract and licensing data to identify rights availability in minutes instead of weeks, and automates moderation workflows to reduce manual checks.
Condé Nast modernized its legacy fragmented infrastructure of 800+ media properties across 22+ brands into a unified AWS Cloud platform.They consolidated data using Databricks on AWS to create a centralized analytics lake house with fine-grained governance, enabling unified insights and real-time analytics across all brands.Deployed AI capabilities with Amazon Bedrock and SageMaker for content rights management and AI-powered content moderation, drastically reducing processing times from weeks to minutes while ensuring editorial standards via Amazon Bedrock Guardrails.Migrated to standardized AWS services including Amazon EKS, Amazon EC2, AWS Control Tower, Lake Formation, and CloudFront to improve operational efficiency, compliance, and scalability.The unified data and AI platform transformed editorial workflows, enabling data-driven decision-making, unlocking historical content assets, and augmenting human creativity rather than replacing it.
Avanade offers its Intelligent Manufacturing solution on Microsoft Azure, focusing on predictive and proactive maintenance for the manufacturing sector. The solution allows for bui...
Kinaxis partnered with Databricks to unify supply chain data and enable smarter, more agile AI-driven decision-making. Their AI-driven Maestro platform integrates data sources to o...
Traditional manual methods for crop disease identification are slow, labor-intensive, and often inconsistent, impacting productivity and sustainability in agriculture.Agentic AI workflows on Databricks allow autonomous agents to analyze imagery and sensor data, detecting diseases, triggering alerts, recommending treatments, and enabling model auto-retraining.The solution uses Databricks AI platform components, including Azure, MLflow, Unity Catalog, Delta Lake, and Apache Spark.The full-agentic architecture ingests streams from drones, satellite imagery, IoT sensors, and mobile apps to process and classify plant diseases in near real-time.Agents operate on multi-agent architectures, collaborating for holistic diagnosis that incorporates environmental, soil, and disease factors.Real-time alerts integrate with dashboards, automating recommended crop protection interventions and scheduling drone inspections.Outcomes include a 40-60% acceleration in disease detection, up to 30% reduction in pesticide usage, improved yields, and higher classification consistency across large-scale operations.The architecture supports continuous feedback and automatic retraining, further improving accuracy and outcomes over time.
Jones Lang LaSalle (JLL), a global real estate services leader, faced challenges from disparate and inconsistent commercial real estate (CRE) data, hindering client insights and operational efficiency. To address this, JLL partnered with Databricks and Microsoft to implement Azure AI Services, including Azure Databricks and a conversational AI analytics layer in its JLL Azara platform.This AI-driven solution aggregates data across portfolios, democratizes insights, and empowers clients to ask complex questions using natural language. What previously took months of engineering can now be done in minutes or seconds, accelerating business intelligence for facility management, workplace trends, and sustainability initiatives. The solution is integrated with JLL Falcon, their proprietary AI platform, leveraging Microsoft's cloud capabilities for security and scale.Since implementation, JLL's clients can measure workplace performance, discover cost savings, and address sustainability goals more efficiently. The platform provides actionable, real-time data, enhancing decision-making at all business levels and across industries.JLL’s collaboration with Microsoft and Databricks exemplifies the use of cloud-based AI analytics to transform real estate services, reduce operational costs, and support rapid, personalized client insights.
Santalucía Seguros, a historic Spanish insurance company, implemented a Generative AI virtual assistant to empower its agents with fast, accurate access to information on insurance products, procedures, and coverages. Available via Microsoft Teams, the assistant uses natural language and is accessible 24/7 across devices, allowing agents to respond instantly to customer queries, thus expediting issue resolution and increasing sales productivity.The system is architected on a Retrieval Augmented Generation (RAG) framework, deployed within Santalucía’s Advanced Analytics Platform running on Databricks and Microsoft Azure. Key innovations include ongoing ingestion and embedding of up-to-date documentation into vector stores, and robust LLMOps for integrating, validating, and rolling out updates without sacrificing response quality or reliability.Databricks Mosaic AI Model Serving enables secure access and management of both Azure OpenAI and 3rd party LLMs, governed by robust workflows and integrated CI/CD. This ensures agility and scalability while maintaining compliance and data privacy.The scalable solution drives greater agent productivity, accelerates customer response times, and supports business growth with measurable improvements in user experience.