From a 3-Hour Quote to a 30-Minute Quote

The Challenge

The business sells support contracts for IT hardware — remote troubleshooting, remote plus replacement parts, or remote plus an on-site technician, paired with a service-level agreement for how fast. Pricing one of those contracts accurately meant manually checking current market prices for the customer's hardware across multiple sources, cross-checking that each result was actually the right part and not an accessory or the wrong variant, then assembling it all into a quote by hand. An average quote took about 3 hours; a large or complex one could take up to 2 days. Every RFQ, price check, and negotiation round lived in scattered emails and spreadsheets, with no single record of what had been quoted, revised, or agreed to.

What We Did

• Built an automated RFQ intake that pulls incoming requests directly from the company's email inbox and document storage, with the original source file always attached and viewable
• Used AI to read RFQ documents in whatever format they arrive and extract structured part number, manufacturer, and quantity data automatically — no manual re-keying
• Built a live pricing engine that checks multiple real-time hardware marketplaces for every line item, with an AI relevance check that filters out accessories and wrong-variant listings a simple keyword search can't tell apart
• Built a versioned quote system — every round of customer negotiation creates a new version instead of overwriting the last, so the full history of what was sent, revised, and approved stays intact
• Added an in-app playbook explaining the company's support-plan and SLA structure, so new team members don't need a separate training manual
• Designed the platform as the foundation for the full sales cycle — quoting today, with purchase orders, contracts, and invoicing next on the roadmap

The Outcome

Quote turnaround dropped from an average of 3 hours to under 30 minutes, and from as long as 2 days to under 30 minutes on the largest, most complex requests — without sacrificing accuracy, since every price now comes from real-time market data instead of memory or a manual lookup. The RFQ-to-quote workflow is live and in active use with the company's team today, as the system moves toward full production rollout.