Powering Efficiencies in a Global Investment Firm with AI and Google Gemini Enterprise
AI-powered search capabilities are driving efficiencies
For a global investment firm, the ability to quickly access accurate information was critical to maintaining a competitive edge. However, their existing internal tools lacked semantic search capabilities and could not retrieve content effectively across siloed systems. This created delays, inefficiencies and data control issues, ultimately slowing down research and decision-making.
Our experts worked with the firm to deliver an AI-powered enterprise search solution built on Gemini Enterprise. Using natural language queries, employees could seamlessly search both structured and unstructured data, drastically improving access to information.
The pilot validated both business value and technical feasibility, achieving a 65% reduction in search time and a 40% decrease in research delays. These results demonstrated clear potential for scaling the solution across the wider organisation.
Our technical approach
Our engagement was structured to ensure both rapid deployment and long-term scalability. The team:
- Conducted discovery workshops to identify user needs and key use cases.
- Deployed Gemini Enterprise and integrated it with Google Cloud Storage, BigQuery and Vertex AI.
- Implemented secure, role-based authentication via Microsoft Active Directory.
- Designed ingestion pipelines capable of handling both structured and unstructured data.
- Delivered onboarding, testing and knowledge transfer to enable the client to fully own and expand the solution.
Transforming search capabilities
By leveraging Gemini Enterprise and Vertex AI, the firm transformed its enterprise search capabilities. The solution not only accelerated discovery and improved decision-making but also set a strong foundation for future AI-driven innovations. As data volumes continue to grow, this approach positions the organisation to unlock even greater value from its proprietary research assets.
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