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The Challenge
Unlocking insights from siloed data systems
- Need for a managed abstraction layer enabling low-code, frictionless access to diverse data sources.
- Difficulty in surfacing relevant insights quickly across structured and unstructured datasets.
- Demand for intuitive enterprise-wide search that enhances employee productivity and accelerates patient-centered innovation.
The Solution
Building a scalable, intelligent search architecture
- Built streaming and batch ingestion pipelines using Google Dataflow to process large datasets.
- Developed automated CI/CD pipelines via Azure DevOps with real-time alerts for pipeline failures to ensure business continuity.
- Leveraged Terraform for infrastructure as code to automate resource provisioning, project setup, and access management.
- Created Cloud Functions for seamless ingestion into Google Vertex AI Agent Builder’s Search App.
- Integrated Prisma and Veracode in DevOps pipeline for continuous vulnerability scanning and compliance monitoring.
Fig 1: Solution Schematic
Value Delivered
Transforming efficiency, insight, and decision-making
|
Outcome |
Impact |
|
Productivity |
Fast, accurate, and contextually relevant search results. |
|
Operational Excellence |
Reduced bottlenecks and improved access to critical data. |
|
Instant Insight |
AI-generated summaries offered quick, actionable understanding. |
Maximizing Gen AI’s potential with ML Ops and integration
This solution showcases how Gen AI can transform search experiences across the enterprise enabling teams to spend less time looking and more time acting. Key learnings:
- Vertex AI and Gemini Pro significantly enhanced the relevance of search results.
- Seamless integration with enterprise DevOps and data infrastructure ensured high adoption and scalability.
