Business Challenge

Our customer is one of the largest automobile manufacturers. Their BigQuery data is vast and growing, restricting data access primarily to SQL-skilled teams across manufacturing, supply chain, warranty, and connected vehicle domains. This created significant challenges for business users in dataset discovery, semantic understanding, table relationships, and informed decision-making. Additionally, manual metadata enrichment consumed significant steward effort and proved unsustainable at scale. These gaps ultimately constrained AI readiness, slowing deployment of predictive and operational intelligence initiatives.

Technology Used

• BigQuery
• Dataplex
• Cloud Run
• Cloud Storage
• Vertex AI Agent Engine
• ADK
• Google Gemini Enterprise
• BigQuery Verse
• Intelligent Metadata Generator

Our Solution and Support

• Deployed BigQuery Verse, an AI-powered agentic data access platform built on Vertex AI Agent Engine and Google Gemini Enterprise
• Implemented a multi-agent architecture including Configuration Agent, Querying Agent, Natural Language Query Engine, Prompt Manager, and ER Generator for autonomous query orchestration and semantic understanding
• Introduced the Intelligent Metadata Generator to automatically create business-friendly, AI-ready metadata for all data assets, eliminating manual enrichment effort
• Integrated with the client’s Dataplex data catalog and internal business glossary to embed automotive domain semantics such as VIN-level schemas, BOM hierarchies, and cross-domain relationships
• Enabled natural language querying to democratize BigQuery access for business users without SQL expertise
• Deployed within the client’s GCP environment on Google Cloud Run with secure access, auto-scaling, and support for 3,000+ concurrent users
• Provided dual access channels via Google Gemini Enterprise and a custom web application for enterprise-wide usability
• Delivered an accelerated implementation timeline, transitioning from infrastructure setup to an insight-ready data platform within 4 weeks

Customer Benefits

• BigQuery Verse evolved into the organization’s primary data access layer, supporting 3,000+ active users through organic, demand-driven usage
• Achieved 95%+ accuracy across complex automotive data domains, improving trust and reducing dependency on technical teams
• Automated metadata generation eliminated 4+ hours/day of manual steward effort, allowing data teams to focus on strategic AI/ML initiatives
• The four-week deployment reduced technical debt and enabled rapid transition from platform setup to actionable insights
• Business and executive stakeholders now move from questions to analytics in minutes rather than sprint cycles, significantly enhancing real-time operational visibility and strategic responsiveness