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Databricks

Delta Lake

Delta Lake is Databricks' open table format providing ACID transactions, unified governance and AI-driven performance optimizations (predictive optimization, liquid clustering) for lakehouse storage. A single copy of source data in Delta Lake or Apache Iceberg can be accessed by any engine, keeping data portable, without vendor lock-in.

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181published use cases
22industries
21countries on record
Predictive Analytics
top AI capability

Evidence mix: High 181 · Medium 0 · Low 0 — bands are computed from each record's evidence signals.

Industry
Country

181 use cases

Real EstateDocument Intelligence

First American Data & Analytics fine-tunes open-source LLMs on Databricks, cutting extraction costs 70%

First American Data & Analytics (DNA), a property-centric information provider to the real estate and title insurance industries, used the Databricks Data + AI Platform to fine-tune open-source LLMs (Mistral, Llama 3, Llama 3.1) for page-level classification and extraction of 100+ data fields from roughly 4 million historical title policy images dating to the 1930s. Using Delta Lake, Databricks Model Training, Managed MLflow, and serverless Model Serving on about 50 GPUs, the team fine-tuned models in two weeks versus the two-plus months it previously took on other platforms. The project cut extraction costs by 70%, reduced project completion time by 75% (months to weeks), and increased the number of data elements extracted tenfold.

First American Data & AnalyticsDelta Lake · Unity Catalog · Mistral +1
Financial ServicesMachine LearningNatural Language Processing

Ophelos uses reinforcement learning and NLP to modernize debt collection

Ophelos, a debt-collection technology company, built the Ophelos Decision Engine, a fully automated ML-powered outbound communication strategy using reinforcement learning to send the best message to each customer at the right time to help resolve their debt, on the Databricks Data + AI Platform with MLflow and Feature Store. It also built OLIVE (Ophelos Linguistic Identification of Vulnerability), an NLP model served via MLflow that scans inbound customer communications to identify people in vulnerable situations. The Decision Engine drove a 25% increase in customers resolving their debts, with 88.3% of customers self-served and 89% rating their experience 4 or 5 stars.

OphelosDelta Lake · MLflow · Databricks Photon +1
Technology & SoftwareRecommendation & PersonalizationPredictive Analytics

Relay42 predicts customer conversion likelihood to power personalized journeys

Relay42, a Customer Data Platform (CDP), uses customer data on the Databricks Data + AI Platform to predict how likely a shopper is to convert; the prediction feeds a decision engine based on anonymized PII to build customer profiles that inform next-best-action messaging. For example, a major Singapore telecommunications client uses this to determine what messages to send shoppers researching phone plans and when. The migration from Hadoop/Cassandra to Databricks cut time to deliver complete customer data from 20-24 hours to 1.5 hours and real-time analytics from 8 hours to about 15 minutes, saving over €180K/year in storage costs.

Relay42Delta Lake
RetailRecommendation & PersonalizationPredictive Analytics

Ahold Delhaize trains ML models for personalization and inventory forecasting across brands

Ahold Delhaize, one of the world's largest food retail groups (7,452+ stores across multiple countries), built a self-service data platform on Databricks Lakeflow Jobs and Auto Loader that lets data engineers across its brands build pipelines for AI/ML needs. Etos uses the platform for machine learning and model training for personalization and inventory forecasting; Albert Heijn's ML engineering team uses Lakeflow Jobs to orchestrate feature engineering and continuous ML model training/retraining pipelines. The platform runs about 1,165 data ingestion jobs daily, cut deployment time 4.5x (1.5 hours to 20 minutes), and reduced costs by 50% through cluster reuse.

Ahold DelhaizeLakeflow Connect · Lakeflow Jobs · Spark Declarative Pipelines +3
ManufacturingPredictive Analytics

Rivian uses machine learning for predictive vehicle maintenance and ADAS

Rivian, an electric vehicle manufacturer, uses machine learning on the Databricks Data + AI Platform to analyze IoT sensor and telemetry data from over 70,000 Electric Adventure Vehicles to power predictive maintenance, addressing potential issues before they affect drivers. Its ADAS team processes telemetric accelerometer data (pitch, roll, speed, suspension, airbag activity) to improve smart driving features like adaptive cruise control and collision warnings. Rivian is also using machine learning to optimize battery efficiency in colder temperatures and improve autonomous driving system accuracy. The platform delivered a 30-50% increase in runtime performance and grew from 250 to 1,000+ platform users in one year.

RivianAgent Bricks · Databricks SQL · Delta Lake +1
Consumer GoodsPredictive Analytics

Barilla uses machine learning for predictive maintenance and supply chain optimization

Barilla, the world's largest pasta producer, uses MLflow on the Databricks Data + AI Platform to operationalize machine learning models across its manufacturing operations. Predictive maintenance models forecast machine failures so maintenance can be scheduled proactively, reducing unplanned downtime, energy use, and emissions. Manufacturing cost deployment models help staff extract and allocate industrial costs and quantify plant losses. The company runs 90% of its business (finance, R&D, manufacturing, supply chain, marketing) on the platform, with 40+ data products in production and 1,000+ dashboards, saving millions of euros in production costs.

BarillaDatabricks Data + AI Platform · Delta Lake · Unity Catalog +1
Financial ServicesPredictive AnalyticsRecommendation & PersonalizationMachine Learning

Personalizing the consumer lending experience

Oakbrook Finance, a UK consumer lending fintech, moved to the Databricks Data + AI Platform on Google Cloud to unify data science and analytics for its loan decisioning platform, O6K, replacing a legacy SQL Server Integration Services environment that could not support advanced risk-prediction analytics. The new platform enabled faster development of data science models for personalized lending decisions, projected 14% cost savings over three years, supported two new financial products launched in 12 months, and is forecast to drive a 5% revenue increase from new top-up loans.

Oakbrook Finance· United KingdomDatabricks Data + AI Platform · Delta Lake · Unity Catalog +1
ManufacturingDigital Twins & SimulationPredictive AnalyticsComputer VisionLarge Language Models

Shaping global infrastructure with ironclad manufacturing

Gerdau, Brazil's largest steel producer, consolidated a complex homegrown open-source data ecosystem onto the Databricks Data + AI Platform, using Delta Lake, Delta Sharing and Unity Catalog to enable real-time processing for digital twin simulations of production lines. The move cut data processing time from 1.5 hours to 12 minutes, delivered a 40% cost reduction for data processing and 80% faster development of streaming solutions, and enabled new AI applications including predictive maintenance, image and text classification, and an LLM-based upskilling assistant for employees.

Gerdau· BrazilDatabricks Data + AI Platform · Delta Lake · Delta Sharing +4
HealthcareLarge Language ModelsDocument IntelligenceFraud & Anomaly Detection

Orizon fine-tunes GenAI models on Databricks to automate 63% of healthcare fraud-detection code documentation

Orizon, a Brazilian health tech fraud-detection company managing 40,000+ medical billing rules, fine-tuned Llama2-code and DBRX models on Databricks using MLflow and Model Serving, and embedded the resulting LLM chatbot into Microsoft Teams via Unity-Catalog-governed data, so business users could get instant rule explanations instead of waiting on C++ developers. The system now automates 63% of documentation workflows, cut documentation time to under five minutes, freed up 1.5 developers, and is estimated to add 1 billion BRL in productivity.

Orizon· BrazilDelta Lake · MLflow · Databricks Model Serving +5
Financial ServicesMachine LearningRecommendation & PersonalizationGenerative AI

Discovery Bank combines ML and GenAI on Databricks to power a hyper-personalized next-best-action banking model

Discovery Bank built a next-best-action (NBA) framework on the Databricks Data + AI Platform, using Delta Lake, MLflow and Unity Catalog, that combines actuarial models, machine learning and generative AI to create a behavioral fingerprint for each client, driving segmentation, pricing, risk management and AI-generated communication templates for client servicing. The NBA model produced a 40% uplift in the impact of customer engagement activities, with data processing 20x faster and data product creation 5x faster than the bank's legacy environment.

Discovery Bank· South AfricaDelta Lake · Unity Catalog · MLflow
Media & EntertainmentAgentic AIConversational AIGenerative AI

Turning 700T Customer Signals into Media Intelligence

MiQ, a global programmatic media partner, built Sigma, an advertising platform on the Databricks Data + AI Platform, to unify more than 700 trillion fragmented customer signals across watching, browsing and buying activity into a single governed intelligence layer. Data flows through a medallion architecture on Delta Lake with Unity Catalog governance, and Databricks SQL serves dashboards, Genie Spaces and agent queries. MiQ built a Planning Agent using two Genie spaces (unified consumer signals and historical campaign data) plus Vector Search to translate natural-language audience descriptions into activation segments, letting non-technical marketers go from audience discovery to media plan recommendations in minutes instead of days. Sigma has powered over 40,000 campaigns for more than 2,300 advertisers since launch, with campaigns returning 2.2x the ROI of standard programmatic campaigns; campaign planning and analysis that once took 6+ hours now takes roughly 5 minutes, and AI-assisted optimization workflows cut storage needs by 50%.

MiQDelta Lake · Unity Catalog · Databricks SQL +3
Technology & SoftwareAgentic AI

From Data Chaos to a Trust Score for Every Table

Databricks' own internal Data Platform team rebuilt data governance across its internal lakehouse of more than 100,000 tables spanning engineering, go-to-market, HR, finance and product telemetry, using Unity Catalog to move from inconsistent, team-by-team access patterns to automatic, measurable governance. The team built a universal classification model tagging every table by sensitivity and domain, an internal system called Fortress enforcing purpose-bound, time-limited access via Unity Catalog's security APIs, and a continuous Data Governance Score (0-100) per dataset covering documentation, reliability and governance, propagated automatically through data lineage. The resulting governance layer now underpins AI agents used across every function at Databricks, from engineering to finance to facilities, letting teams check a dataset's governance score before using it to train a model instead of running manual reviews.

DatabricksUnity Catalog · Lakeflow Connect · Databricks Apps +3
Financial ServicesPredictive AnalyticsConversational AIAgentic AI

Delivering One Highstreet Experience Through Connected Data and Intelligence

Highstreet Insurance Partners, an insurance brokerage that has grown through partnerships with more than 200 independent agencies, built Ora, a proprietary unified digital intelligence platform on Databricks that combines trusted data, analytics, intelligent automation and AI. Ora manages more than 49 billion data points spanning client, policy and carrier history for roughly 500,000 active client relationships. Highstreet built a knowledge graph connecting clients, policies, coverages, documents, and communications to ground AI agent recommendations, uses Unity Catalog for governance across data and ML assets, and Databricks Model Serving to run machine learning models that surface renewal-likelihood scores and cross-sell opportunities. Highstreet reduced the time to onboard a new agency partner's data into Ora from as much as six months to less than two weeks, and increased daily data refresh success from 35% to more than 95% after re-engineering Ora's data foundation with Lakeflow pipelines and Delta Lake.

Highstreet Insurance Partners· United StatesUnity Catalog · Delta Lake · Lakeflow Jobs +2
HealthcarePredictive AnalyticsConversational AI

Keeping Every Patient Healthier as Fast as Care Demands

Duly Health and Care, the largest multi-specialty physician-owned practice in the U.S., migrated from a 17-year-old SQL Server warehouse to the Databricks Data + AI Platform, unifying nearly 60 data sources including Epic and Workday via Delta Lake and Unity Catalog. Duly's data science team used MLflow and AutoML to build a hospital readmission prediction model, comparing Random Forest, LightGBM and XGBoost algorithms, trained on 100,000 historical patients and achieving a ROC AUC of 89.2%. The company also built a conversational "Physician Finder" tool integrated into its Epic workspace, and five Genie Agents (Patient, Provider, Finance, HR, Appointments) letting non-technical staff query live data in plain English. Duly reports a 29% drop in hospital readmission rates (14% to 10%), saving an estimated $4.5 million annually, a 30% reduction in data platform costs versus SQL Server, and roughly double the number of data projects completed in 2025 versus 2024 with the same headcount.

Duly Health and CareDatabricks SQL · Delta Lake · Unity Catalog +3
EnergyGenerative AI

Accelerating the Path to Net Zero with Energy Insights

SSE Airtricity, an energy supplier serving around 750,000 customers in Ireland, built the in-house Enhanced Smart Insights (ESI) Energy Advisor on the Databricks Data + AI Platform, delivering personalized energy-saving advice to over 65,000 smart meter customers, such as guiding EV owners toward off-peak charging. The advisor is built on Anthropic's Claude Sonnet 4.5, accessed via Databricks AI Model Serving, with Lakeflow Spark Declarative Pipelines processing billions of rows of smart meter data nightly and Unity Catalog governing data and AI models. The team used MLflow's GenAI evaluation framework to implement automated AI "judges" that reject and regenerate failing insights before they reach customers. SSE Airtricity went from concept to production in about four months; within the first month it saw a 12% increase in unique visitors to the insights section, and 90% of logged-in customers now engage with the personalized insights.

SSE Airtricity· IrelandClaude Sonnet 4.5 · Databricks AI Model Serving · MLflow +3
Financial ServicesPredictive Analytics

Transforming Data Pipelines to Power Faster Credit Decisions

Capital One's data and engineering teams built a centralized Feature Hub on Databricks, using Photon as the compute engine and Delta Lake as the foundation, to serve as a single environment for historical and operational feature pipelines supporting its credit line increase program and credit decisioning models. The hub curates records across millions of accounts to provide a unified customer view for both modeling and daily decisioning. Capital One reports 60x faster compute performance for large-scale backfills and an 80% decrease in time and cost per job after migrating production pipelines to Databricks, shortening feature development and deployment from prior timelines to weeks.

Capital OnePhoton · Delta Lake
Technology & SoftwareAgentic AIConversational AI

Inside the Governed Data Platform Powering ChatGPT: OpenAI on Databricks

OpenAI runs its marketing, analytics, security, and finance operations on the Databricks Data + AI Platform across Azure and AWS, with usage data landing in Delta tables governed by Unity Catalog. OpenAI's Security team uses Databricks streaming pipelines to standardize infrastructure, cloud, and vendor audit logs into governed Delta tables for threat detection, investigation, and incident response, including Codex agents querying governed security data via SQL APIs. The marketing team uses a Bronze-Silver-Gold architecture to build audiences without writing SQL for one billion weekly active users, eliminating $400,000 per month in storage costs. Separately, Databricks and OpenAI announced a multi-year partnership bringing OpenAI's frontier models, including GPT models and Codex, natively into the Databricks Data + AI Platform, callable via SQL or API against data governed by Unity Catalog.

OpenAIAgent Bricks · Databricks SQL · Delta Lake +2
Media & EntertainmentConversational AI

Amagi Ensures Millions Never Miss Their Shows

Amagi, a media technology company supporting 8,000+ streaming channels and 300+ distributors, consolidated fragmented data systems (Dataproc, Snowflake, and in-house platforms) across AWS and GCP into the Amagi Data Platform (ADP), a unified lakehouse built on Databricks with Unity Catalog governance. The platform serves real-time data for ad decisioning, content performance analytics, billing and customer reporting to internal teams (via notebooks, Genie, SQL warehouses) and customer-facing products. Amagi reports 45% cost savings from consolidating fragmented data systems, 15x faster time to market for new data products, and 35% fewer production incidents due to improved data reliability.

AmagiDatabricks SQL · Delta Lake · Spark Declarative Pipelines +2
Financial ServicesPredictive Analytics

ABN AMRO's financial services digital transformation at a global scale with Databricks

ABN AMRO, the third-largest bank in the Netherlands, moved from a centralized on-premises data warehouse and siloed teams to the Azure Databricks Data + AI Platform, operationalizing it within a couple of months. The platform, using Delta Lake for reliable data pipelines and MLflow for deploying machine learning models, gave over 500 engineers, scientists and analysts shared access to data. ABN AMRO uses the platform for machine learning-based fraud detection to identify anomalous behavior such as money laundering, a marketing automation stack for faster, more relevant customer product recommendations, and a client dashboard giving support teams a near real-time view of customer assets and transactions. The bank delivered its use cases 10 times faster than with its previous infrastructure, with over 100 additional use cases planned.

ABN AMRO· NetherlandsDatabricks Data + AI Platform · Delta Lake · MLflow +2
Financial ServicesFraud & Anomaly DetectionRecommendation & Personalization

Maya is simplifying banking for diverse populations

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.

Maya· PhilippinesDatabricks · Delta Lake · Unity Catalog +3
EducationMachine LearningFraud & Anomaly DetectionAI Model Development & MLOps

GoGuardian: Safer schools, empowered teachers, thriving students

GoGuardian, which powers safe, focused learning for half of U.S. K-12 students, migrated its ML infrastructure to Databricks to manage billions of daily inferences for web filtering, classroom management and harm prevention while maintaining a PII-free, COPPA/FERPA-compliant data environment. Using Delta Lake, Lakeflow, Unity Catalog, MLflow and Databricks Model Serving, GoGuardian achieved up to 50% reduction in machine learning operational costs, 90% operational cost savings with its Delphi website classification model, and a 62% reduction in inappropriate device use among students. AI-driven prioritization also cut the volume of records requiring human review for high-risk content by over 95%, from 1 million to 35,000-45,000.

GoGuardian· United StatesDelta Lake · Databricks Lakeflow · Unity Catalog +6
RetailComputer VisionGenerative AILarge Language Models

Furniture.com Transforms Online Search with Databricks

Furniture.com unifies over 60 retail partners and 1.5 million SKUs on the Databricks Data + AI Platform, using Delta Lake, MLflow and Unity Catalog to run its ML lifecycle. Its Find It AI product-discovery tool uses generative AI to create a synthetic image representing shopper intent, then matches it against the product catalog for image-based search. A Collections model uses LLMs to automatically group related products, finding more than 16,000 collections across 50+ partners with no human intervention. Users who interact with Find It AI show a click-through rate 8x higher than baseline and a return rate 3.2x higher than baseline.

Furniture.comDatabricks Data + AI Platform · Delta Lake · MLflow +3
TelecommunicationsMachine LearningConversational AI

Building the foundation for the 5G revolution: Digital Nasional Berhad

Digital Nasional Berhad (DNB), Malaysia's government-established 5G network operator, used the Databricks Data + AI Platform to build a cost-effective, high-performance data platform to process 5G network data at scale, achieving 82%+ populated-area coverage in two years. Using Delta Lake with a medallion (Bronze/Silver/Gold) architecture, Databricks Workflows for pipeline orchestration, serverless compute, Notebooks for team collaboration, Unity Catalog for governance, and MLflow for ML lifecycle management, DNB achieved 70% cost optimization and a 60-70% increase in data pipeline performance, and has begun building AI-powered chatbots giving network engineers real-time access to performance insights with geospatial visualizations.

Digital Nasional BerhadDatabricks Data + AI Platform · Delta Lake · Databricks Workflows +3
ManufacturingPredictive AnalyticsMachine LearningAgentic AI

TK Elevator: Moving Beyond with Data + AI Driven Service Intelligence

TK Elevator (TKE), one of the world's largest providers of elevators, escalators and vertical transportation systems, adopted the Databricks Platform to unify and process more than 500 million IoT telemetry events daily from connected elevators across 30+ countries, moving from reactive to predictive maintenance. TKE's MAX platform generates predictive insights that feed actionable guidance to field technicians via its Digital Operations Center (DOC), which generates 30,000-40,000 tickets annually and has reduced technician troubleshooting time on call-backs and unplanned shutdowns by up to 20%. The platform scaled from 3 to over 40 markets (10x expansion), cut data pipeline delivery from months to weeks, and reduced data sharing time with internal/external consumers from three months to three days (90% reduction). TKE uses Delta Lake, Delta Sharing, Lakeflow, Unity Catalog, Databricks Assistant, MLflow, AI Gateway, Vector Search and Model Serving, and is exploring agentic AI to combine technical, service and commercial context in real time.

TK ElevatorDelta Lake · Delta Sharing · Lakeflow +6
Financial ServicesMachine LearningGenerative AINatural Language Processing

Techcombank: Ushering Personalized Banking for Millions of Customers

Techcombank, Vietnam's largest private financial institution with 315 branches serving over 15.3 million customers, adopted the Databricks Data + AI Platform to unify data from disparate on-premises databases and a legacy data warehouse. Central to the initiative is 'Customer Brain,' a customer-360 tool centralizing customer data for targeted marketing, and the Lead Allocation Curated Engine (LACE), which uses AI insights to prioritize and assign sales leads. Techcombank built machine learning models for fraud detection and credit risk management, using an enterprise feature store with over 7,500 features and more than 100 ML risk models to manage a credit lifecycle handling a twentyfold increase in retail credit applications. MLOps on Databricks with MLflow cut model implementation from months to weeks. The bank is developing an internal RAG-based chatbot, Smartie, built on Databricks AI Search, and piloting AI/BI Genie for natural-language data queries. The platform has over 1,000 active users bank-wide.

Techcombank· VietnamDatabricks Platform · Delta Lake · MLflow +4
EnergyPredictive Analytics

From high costs to near real-time insights with Zerobus Ingest

Beusa Energy, a 30-year energy sector company spanning electric hydraulic fracturing, mobile power generation, electrical distribution, field gas processing and industrial manufacturing, migrated its high-frequency telemetry ingestion from a custom SQL Statement API pipeline to Databricks' Zerobus Ingest direct-write API. The migration required only swapping the write path (same .NET worker, same MQTT subscriptions), cutting ingestion cost from roughly 689 DBU per GB to about 0.29 DBU per GB, a 99% cost reduction, while eliminating the need for a separate streaming broker tier. Today more than 6,000 devices stream telemetry at 1 Hz across about 250 remote assets, ingesting ~22 million rows daily into a unified lakehouse with end-to-end latency of about three seconds, governed by Unity Catalog. Beusa is now using this high-frequency telemetry, combined with maintenance history, to train predictive-maintenance models forecasting remaining useful life of assets, moving from condition-based to predictive and eventually prescriptive maintenance.

Beusa EnergyDatabricks Zerobus Ingest · Delta Lake · Unity Catalog +2
ManufacturingRetrieval-Augmented GenerationConversational AINatural Language Processing

Lippert Improves Customer Support with GenAI

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.

LippertDatabricks · Agent Bricks · Unity Catalog +5