Multi-Agent AI Co-pilot for Smarter Relationship Management

Industry context

In private wealth management, Relationship Managers play a critical role in delivering personalized advisory services. However, as businesses scale, the complexity of accessing timely insights and executing workflows increases significantly.

The problem

RM workflows were fragmented and heavily dependent on multiple systems:

• Key information such as research, reports, and portfolio data was scattered across platforms
• RMs spent significant time navigating systems instead of engaging clients
• Operational tasks required coordination with backend teams
• Client requests often experienced delays due to manual dependencies

This resulted in reduced responsiveness, underutilization of insights, and limited ability to deliver timely, high-quality advisory recommendations during client interactions.

Our role

Ganit designed and implemented a GenAI-powered multi-agent co-pilot that enabled RMs to access information, execute workflows, and deliver advisory actions seamlessly through a unified conversational interface.

Methodology

1. Multi-Agent Architecture - A coordinated system of AI agents was developed to handle complex workflows.

2. Conversational Interface with Execution - Natural language interaction combined with structured execution.

3. Deep System Integration - Direct execution of tasks like report generation and service requests.

4. Context-Aware Intelligence - Persistent context across interactions.

Enabling consumption

• Instant access to research and portfolio insights
• Real-time execution of workflows
• Proactive portfolio alerts
• Unified interface for all tasks

Our impact

The co-pilot transformed RM workflows into a unified, execution-first system.

• Tasks completed instantly instead of hours
• Improved advisory quality
• Better responsiveness during interactions
• Enhanced churn prevention capabilities