AI Agent-Powered RFQs: Real-Time Quoting Without the Manual Mess

Client Overview

Our client is a mid-sized manufacturer that handles dozens of request-for-quote (RFQ) documents every day all around the world. Until now, the team has relied on spreadsheets, old email chains, and out-of-date software, so that scattered info, endless copy-paste tasks, and separate supplier files keep slowing them down. Their wish is simple: create a fresh real-time AI tool that reads each RFQ, finds the right suppliers, gathers prices, and sends back answers-without disturbing the way people already work.

Challenges

• Manual Data Extraction from RFQs: Team members read emails, extracted product specifications manually, and formatted them into spreadsheets-wasting time and admitting errors.

• Fragmented Supplier Knowledge: Historical supplier data lay buried in Airtable, while new prospects sat elsewhere. This disconnection thwarted quick, informed decisions.

Solution

• • AI Agent-Enhanced RFQ Parsing: Google Gemini extracted crucial line items from emails and PDFs, transforming messy, unstructured RFQs into clean inputs ready for JSON in Airtable.

  • Supplier Discovery + Smart Drafting: Historical suppliers were suggested via Airtable, whereas Gemini pulled new ones from Google Sheets. AI-prepared emails were pre-drafted for team approval and send-off.

Business Impact

• • • Seamless Procurement Workflows, Zero Manual Lag: Henceforth, RFQ administration became real-time orchestration-from intake through to final quote capture-with the back-and-forth hours lost in manual formatting.

    • Smarter Buying Decision With Greater Data Confidence: Teams gained views on price histories and supplier metrics, thus enhancing transparency, negotiation power, and multi-team collaboration.