From RFQ to Signed Proposal in Five Minutes: Automating the Quote Process
An industrial client processed ~15 RFQs a day, each taking an hour of manual work. We automated intake, pricing, and quotation — dropping it to 2.5 minutes per RFQ with 95% less manual effort.
When we started working with an industrial manufacturer, the technology wasn't the problem. The manual effort between the systems was. This is how we turned that friction into an automated workflow — and what it changed.
The Problem
- ~15 RFQs a day, each needing ~60 minutes of manual work
- Document review, product validation and pricing done by hand
- Multiple manual handoffs and approval delays
- High risk of errors and slow response times losing deals
What We Automated
Rather than rip out the tools the team already relied on, we connected them with AI agents that handle the repetitive work end to end:
Document understanding
AI reads the RFQ and extracts specs automatically.
Automated pricing
Rates are pulled straight from the ERP or rate card.
Branded proposal generation
A ready-to-sign quotation is produced instantly.
Approval routing
The proposal lands in the owner's queue before the competitor has opened the email.
The Results
- Time per RFQ cut from ~60 minutes to ~2.5 minutes
- Less than 40 minutes of human oversight per day
- 95% reduction in manual effort
- Faster responses and higher win rates
Why It Matters
The biggest value of AI here isn't replacing employees — it's letting the team spend time on customer relationships instead of repetitive quoting.
Could This Work in Your Business?
If you're already running a CRM, ERP, WhatsApp or any business software, there's a good chance you're using a fraction of its potential — and losing hours to the gaps between systems. In a free 30-minute AI automation audit, we map your workflows and show you exactly where time and money are leaking, and what to automate first. You keep the plan either way. Book your free automation audit.
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About the Author
Darshan R Krishnan
COO at Boostmysites — helping businesses scale with systems, not headcount.
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