47Billion developed a multi-agent AI simulation platform for a leading financial services firm to modernize sales representative training. The solution enabled reps to practice real-time, persona-driven conversations with intelligent feedback and contextual support. Powered by RAG and OpenAI, it personalized learning and accelerated onboarding. The platform led to a 20% increase in closure rates and 60% faster ramp-up for new hires. It transformed traditional training into a scalable, data-driven performance accelerator.
Client Challenge
A prominent financial services and investment management firm needed a scalable way to continuously upskill its widespread salesforce. Traditional training methods and LMS systems were falling short — unable to keep pace with:
- Constantly evolving financial products
- Diverse and complex customer personas
- Stringent compliance and regulatory demands
The client required a realistic, intelligent simulation environment that could mimic live sales conversations, provide instant feedback, and reduce dependence on manual coaching.
The AI Agent Solution
We engineered a multi-agent AI-driven sales training platform designed to simulate complex financial sales conversations. Acting as a virtual sparring partner, the platform provides personalized, feedback-rich simulations to boost real-world readiness.
Key Features
Multi-Agent Roleplay Engine
A triad of intelligent agents creates immersive, real-time training sessions:
- Salesperson Agent (User): The trainee engages in a dynamic, text and voice-based pitch.
- Financial Persona Agent: Emulates clients (e.g., HNIs, conservative investors), using CRM and product data to respond authentically.
- Sales Helper Agent: Offers smart nudges, rebuttal cues, and reference snippets from internal playbooks.
Knowledge-Driven RAG Layer
- Integrates Retrieval-Augmented Generation (RAG) via Azure AI Search
- Pulls contextual data from internal product guides and competitor documentation
- Enables informed and accurate responses during simulation
Scenario Customization Engine
- Tailors simulations across different customer archetypes, tone preferences, and complexity levels
- Helps sales reps practice objection handling, upselling, and customer psychology navigation
Intelligent Feedback Loop
Post-simulation reports assess:
- Tone, empathy, and fluency
- Product knowledge accuracy
- Objection-handling and conversion triggers
Promotes continuous, adaptive learning at scale.
Technology Stack
- Frameworks: Azure AI Foundry, Autogen, PromptFlow
- Vector Search: Azure AI Search
- Memory Management: Mem0
- Generative AI: OpenAI APIs
- Observability: Langfuse
- Frontend: Flutter
- Backend: Python
Business Impact
- 20% Increase in closure rates across trained sales reps
- 40% Boost in call quality and objection-handling effectiveness
- 60% Faster onboarding for new hires through automated, repeatable simulations
- 30% Quicker product rollout across sales teams