Back to Directory
Databricks Platform logo

Databricks Platform

5 use cases using this technology

Financial ServicesAgentic AIConversational AI

Erste Group Bank builds a conversational AI Governance agent on Databricks, replacing ticket-based EU AI Act compliance processes

Erste Group Bank AG

Erste Group Bank AG, one of the largest retail banks in Central and Eastern Europe, built an Agent for AI Governance on the Databricks platform, showcased at the Data + AI World Tour in Munich. The bank replaced ticket-based processes with a conversational compliance AI assistant: users can "just talk," and the system automatically structures, validates and enriches their input for AI-governance stakeholders, producing reviewer-ready packets covering EU AI Act obligations, security, data protection and architecture while maintaining an auditable trail.

Financial ServicesMachine LearningConversational AI

TBC Bank Operationalizes Trusted Data with Lakebase

TBC Bank

TBC Bank, the largest banking group in the Caucasus region, built a Lakehouse on Databricks and adopted Lakebase and Databricks Apps to move from on-premises SQL Server instances and month-long reporting cycles to self-service analytics and AI-driven applications, including a web-based AI chatbot and AutoML-based credit risk scoring. Credit risk model deployment fell from 14 weeks to two days, and more than 600 users regularly query governed data through Genie.

Technology & SoftwareRetrieval-Augmented GenerationAI Model Development & MLOps

Zapier Powers Real-Time Customer Experiences with Databricks

Zapier

Zapier unified its data on the Databricks Platform to enable self-serve, AI-powered analytics across product, marketing, sales and support. Using the Databricks MCP connector built on Unity Catalog, AI agents get governed real-time access to Zapier's data; Vector Search handles over 600k requests per day for semantic search and RAG-based knowledge retrieval; MLflow and Model Serving operationalize ML workflows. Dashboard creation time dropped from 2-3 days to a few hours, and the share of data queries executed via AI-assisted workflows grew from 0% to roughly 75% within 6-9 months.

Financial ServicesMachine LearningGenerative AINatural Language Processing

Techcombank: Ushering Personalized Banking for Millions of Customers

Techcombank

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.

Travel & HospitalityRecommendation & Personalization

TMAP Mobility Powers Smarter, Safer Travel

TMAP Mobility

TMAP Mobility, Korea's leading mobile navigation service with over 25 million subscribers and adoption in more than 95% of domestic vehicles, adopted the Databricks Platform to address data access and governance roadblocks that stalled AI-driven personalization efforts. Using Genie Space, non-data specialists can now explore and analyze data with natural language, and Unity Catalog provides granular permission management and column masking. As of September 2025, the analytics team receives 68% fewer simple data extraction requests, and approximately 48% of all employees can directly explore and utilize data. TMAP processes more than 7.3 billion mobility data points annually and used the Recommendation Engines Solution Accelerator to prototype and deploy scalable recommendation models faster.