Request-for-quote intake is often a quiet drain on sales and operations teams. Emails arrive with part numbers, drawings, due dates, quantities, and special instructions scattered across messages and attachments. UiPath can automate much of this work, but the design choice matters: rules-only automation or AI-assisted review.
The rules-only approach
A rules-only UiPath workflow works best when RFQs are consistent. For example, a customer always sends the same spreadsheet template, uses standard item codes, and includes required fields in predictable columns.
Advantages:
- Lower complexity to build and maintain
- Clear pass-or-fail validation rules
- Easy audit trail for what the bot checked
- Strong fit for repeat customers with standard formats
Tradeoff: rules-only bots struggle when customers send free-form emails, PDFs, screenshots, or incomplete details. The bot may push many items to manual review, reducing ROI if exceptions are frequent.
The AI-assisted approach
An AI-assisted UiPath workflow can classify RFQ emails, extract details from unstructured attachments, identify missing information, and summarize key requirements for the quoting team.
Advantages:
- Handles more customer formats without a custom rule for each one
- Reduces time spent reading long email threads
- Can flag drawings, due dates, quantities, and special terms for review
- Improves intake speed when RFQ volume is varied
Tradeoff: AI should not be treated as a final decision-maker for every quote. Human review is still useful for unusual specifications, high-value opportunities, or ambiguous customer language.
Where ROI usually comes from
The payoff is not just fewer keystrokes. Better ROI often comes from faster quote assignment, fewer missed RFQ deadlines, cleaner data in CRM or ERP systems, and less time spent asking customers for information that should have been identified at intake.
Track these before and after automation:
- Average minutes to log and assign an RFQ
- Number of RFQs waiting in shared inboxes
- Percentage of requests missing required details
- Manual rework caused by incorrect item, quantity, or due date entry
- Cycle time from RFQ receipt to quote owner assignment
A practical recommendation
For many businesses, the best option is not rules-only or AI-only. Start with rules for known templates and required field checks. Add AI for classification, extraction from messy documents, and exception summaries.
This blended model keeps automation controlled while expanding coverage. It also gives business owners a clearer ROI story: predictable RFQs move straight through, while complicated requests reach the right person with better context and less administrative work.
