The automotive retail industry faces critical challenges such as inconsistent service quality, limited availability, outdated information, and high training costs. Our vision was to create an AI assistant that delivers consistent, professional sales service 24/7 while maintaining real-time inventory accuracy.

Maestro leverages cutting-edge RAG (Retrieval-Augmented Generation) technology to provide:

• 24/7 car sales consultations with inventory-based recommendations.
• Professional, natural interactions tailored to customer needs.
• Special case handling, such as $0 prices or unavailable inventory.
• Guidance through the sales process using proven, professional techniques.

Maestro combines:

• RAG technology OpenAI API as Genetor and self made sentence transformer as retiever.
• A five-layer prompt architecture for structured and natural interactions.
• Sentence transformers to intelligently search and recommend from inventory.
• Professional sales knowledge integration for consistent and expert-level service.
• Context management to maintain conversational flow and relevancy.
• OpenAI API as Genetor and self made sentence transformer as retiever.

1. Balancing similarity thresholds for relevant recommendations.
2. Effective conversation context management for natural flow.
3. Ensuring natural and fluent interactions.
4. Overcoming the model illusion issue.

• Seamlessly integrating RAG with professional sales expertise.
• Innovating a five-layer prompt architecture for structured interactions.
• Creating a highly interactive and engaging design.

1. Multimodal support for visual car comparisons.
2. Enhanced personalization capabilities to tailor recommendations.
3. Real-time inventory synchronization for accuracy.
4. Multi-language support to cater to a global audience.
5. Possaible migration to the langGraph framework to intergrate agentic workload to out application.
6. Implement interface for users to upgrade car inventory list.

#UI Photos