The client’s quote management process was inefficient due to highly unstructured RFQ submissions and complex multi-layer quotation workflows. Customers provided RFQs in diverse formats like Excel sheets, tabular PDFs, plain emails, and custom templates, leading to human errors, slow vendor communication, and delayed responses. Additionally, their dual-sourcing model required coordinating internal inventory checks and third-party vendor quotes, consolidating pricing, and ensuring margin accuracy. The lack of centralized tracking made monitoring progress, bottlenecks, and reporting difficult. Fragmented inputs, complex coordination across sales and vendors, and limited visibility created inefficiencies, increased errors, and reduced responsiveness. A transformative approach was required to modernize RFQ processing. The platform is architected for continued evolution and enhancement: Advanced AI Capabilities: Integration of newer LLM models for improved accuracy Predictive Analytics: AI-driven insights on pricing trends and vendor performance Mobile Access: Native mobile apps for on-the-go RFQ management Expanded Integrations: Direct ERP and accounting system connections Machine Learning Optimization: Continuous improvement of product mapping accuracy Customer Portal: Self-service RFQ submission and tracking for customers Analytics Dashboard: Business intelligence and performance reporting