Toptal uses AI to boost RFQ automation accuracy from 75% to 96% for supply chain consultancy.
A supply chain consultancy partnered with Toptal to automate complex request for quote (RFQ) processing with AI, reducing manual data entry while improving extraction accuracy.
Client
A US-based supply chain company processing high volumes of RFQs and quotations for industrial customers.
Employees
Revenue
Industry
Business ServicesDelivered Services
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RFQs arriving by email required employees to manually enter critical contact and quotation data, creating a slow, error-prone process complicated by information arriving across multiple document formats.
Solution
AI-powered RFQ Processing
Toptal built a Python automation system using AWS Bedrock and Claude to extract contact and line-item data from emails, documents, spreadsheets, and images.
Multilayer Data Validation
PyTest supported iterative validation, while repeated AI queries and database cross-checks helped identify inconsistent results and verify extracted product and contact information.
Outcome
Improved Extraction Accuracy
Testing with real-world RFQs increased overall automation accuracy from approximately 75% to 96%, substantially reducing the manual intervention required to process quotations.
Better Contact Accuracy
Contact extraction reached 100% accuracy during testing, while more reliable RFQ processing accelerated quotation turnaround and increased confidence in data integrity.
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