{"slug":"deutsche-bank-builds-db-lumina-a-rag-research-agent-that-saves-analysts-up-to-two-hours-per-report","url":"https://findausecase.com/use-cases/deutsche-bank-builds-db-lumina-a-rag-research-agent-that-saves-analysts-up-to-two-hours-per-report","title":"Deutsche Bank builds DB Lumina, a RAG research agent that saves analysts up to two hours per report","description":"Deutsche Bank Research built DB Lumina, an AI research agent on Google Cloud (GKE, Vertex AI Gemini models, Cloud SQL pgvector, Discovery Engine RAG) that lets analysts chat with documents, use standardized prompt templates, and ground answers in enterprise knowledge with inline citations. Since going live in September 2024, DB Lumina has reached about 5,000 users across Deutsche Bank Research, saving analysts 30-45 minutes preparing earnings note templates and up to two hours writing research reports and roadshow updates, with one analyst increasing report analysis depth by 50%.","company":"Deutsche Bank","industry":"Financial Services","aiCapabilities":["Retrieval-Augmented Generation","Generative AI","Large Language Models"],"technology":["Google Kubernetes Engine","Vertex AI","Cloud SQL","Cloud Storage","Dataflow","Discovery Engine API","Cloud Natural Language APIs","Gemini"],"deployment":"Public Cloud","problemStatement":"Deutsche Bank Research analysts relied on painstaking manual work to create research reports: sifting through and gathering data from financial statements, regulatory filings and industry reports, then synthesizing vast amounts of information to build financial models and identify patterns, which limited the depth of analysis and range of topics analysts could cover.","solutionApproach":"Deutsche Bank built DB Lumina with a gen AI-powered chat interface using Google's Gemini foundation models, prompt templates for consistent document processing, and a retrieval-augmented generation architecture grounding responses in enterprise knowledge sources with inline citations, built on GKE, Cloud SQL with pgvector, Cloud Storage, Dataflow, Vertex AI and the Discovery Engine API, with guardrailing techniques for compliant outputs.","businessValue":"Since going live in September 2024, DB Lumina reached about 5,000 users across Deutsche Bank Research, saving analysts 30 to 45 minutes preparing earnings note templates and up to two hours writing research reports and roadshow updates, with one analyst increasing the analysis depth of an earnings report by 50% and improved editorial and grammatical accuracy in analyst notes.","evidence":{"band":"high"},"sourceUrl":"https://cloud.google.com/blog/topics/financial-services/deutsche-bank-delivers-ai-powered-financial-research-with-db-lumina","dates":{"publishedAt":"2026-09-16T09:05:26.275Z","publishedAtSource":"pipeline","updatedAt":"2026-09-16T09:05:26.275Z"},"license":"Open for reading and citing with a link to https://findausecase.com/use-cases/deutsche-bank-builds-db-lumina-a-rag-research-agent-that-saves-analysts-up-to-two-hours-per-report. Bulk republication requires permission."}