Manufacturing · Operations
⚙️ AI Workflow Automation

AI-Generated RFQ Forms from Unstructured Customer Emails

How a manufacturing company eliminated manual RFQ processing — cutting turnaround from hours to 28 seconds with near-zero errors.

5×
Faster RFQ turnaround vs manual process
~0
Manual errors on AI-generated RFQs
28s
Time to generate a complete RFQ from raw email
100%
Sales team hours reclaimed from admin
— The Situation

The challenge and the solution

// The Challenge

Customers send rough descriptions. Sales teams spent hours turning them into quotes.

A manufacturing client received dozens of customer enquiries daily — unstructured emails describing what they needed in plain language. Sometimes with attachments, sometimes just a paragraph of text. A sales team member had to read each email, interpret the requirements, cross-reference the product catalogue, and manually fill in a Request for Quotation form before a quote could be produced.

  • Average RFQ creation time: 45–90 minutes per request depending on complexity
  • High error rate — misinterpreted specifications, wrong product codes, missed quantities
  • Sales team spending 30–40% of time on admin rather than selling
  • Delayed response times damaging competitiveness — customers expecting same-day quotes
  • Scaling was impossible — more volume meant more headcount, not more automation
// The Solution

AI interprets the email, extracts specifications, and generates the RFQ in 28 seconds.

We built an AI workflow that reads incoming customer emails using GPT-4, extracts all specification data regardless of how it's phrased, cross-references the product catalogue, and generates a complete, accurate RFQ form — ready for the sales team to review and send in under 30 seconds.

  • Email received → AI reads and interprets customer intent and specifications
  • Product catalogue cross-referenced to identify correct SKUs and pricing
  • Complete RFQ form generated with all fields populated accurately
  • Sales rep reviews in CRM, approves, and sends — no re-keying
  • Edge cases and ambiguous specs flagged for human clarification only
— What We Built

Six components of the solution

Every piece designed to solve a specific part of the problem — integrated into one system that works end-to-end.

🧠

LLM Specification Extraction

GPT-4 reads raw email text and extracts: product type, dimensions, quantities, delivery deadline, and any special requirements — regardless of how loosely they're described.
🔗

Product Catalogue Integration

Real-time API connection to the product database. AI matches extracted specifications to correct SKUs, checks availability, and retrieves current pricing automatically.
📋

RFQ Form Generation

Structured RFQ form populated with all extracted and matched data. Incomplete or ambiguous fields flagged clearly — sales rep only touches exceptions.
✉️

Email Trigger & CRM Routing

Incoming emails auto-detected, processed, and the generated RFQ routed to the right sales rep in the CRM with the original email attached for context.
📊

Error Flagging & Confidence Scoring

Every extracted field has a confidence score. Low-confidence extractions are highlighted for human review — ensuring accuracy without removing human oversight on complex cases.
⚡

End-to-End in Under 30 Seconds

From email received to RFQ ready in the sales rep's queue: 28 seconds average. What previously took 45–90 minutes now takes less time than reading the original email.
— Results

What this delivered for the client

The numbers — measured outcomes

5×
Faster RFQ generation — from 45–90 minutes to 28 seconds end-to-end
~0%
Error rate on AI-generated RFQs — validated against product catalogue at point of generation
30h
Per week returned to the sales team — redirected from admin to active selling
Same-day
Quote turnaround achieved — where previously customers waited 1–2 days
✓
Sales team focused on closing, not admin

With RFQ generation automated, the sales team shifted from spending half their day on form-filling to focusing entirely on relationships, negotiations, and closing.

✓
Customer response times improved dramatically

Same-day quote turnaround became the standard. Previously a competitive weakness — now a differentiator. Several new clients cited response speed as a reason for choosing the company.

✓
Zero system replacement

The AI layer was built on top of existing email infrastructure and the existing product catalogue database. No ERP migration. No new CRM. Implementation disruption: zero.

"The RFQ automation they built saves us 5 hours every single day. I will never switch to any other company."
S
Salvatore
Manufacturing Client · Europe
— Delivery Timeline

How we delivered it

From the initial audit to live deployment — every stage designed to minimize risk and maximize speed to value.

Week 1–2
🔍

AI Audit & Process Mapping

Mapped the full RFQ workflow. Analysed 200 historical customer emails to understand variation in how customers describe requirements. Identified edge cases and ambiguity patterns.
Week 3–4
⚙️

LLM Pipeline Build

Prompt engineering for specification extraction. Product catalogue API integration. Confidence scoring system. Initial testing against historical emails — 91% accurate from day one.
Week 5–6
🔗

CRM Integration & Testing

Connected AI output to CRM. Built the sales rep review interface. Parallel run — AI and manual side by side for two weeks. Accuracy validated against human-generated RFQs.
Week 7
🚀

Live Deployment

Full go-live. AI handling 100% of incoming RFQ emails. Sales team reviewing AI-generated forms rather than building from scratch. Average processing time: 28 seconds.
— Technology stack
OpenAI GPT-4 Python · FastAPI REST API Integration CRM Webhook Product Catalogue DB Email Parser

Want a similar result for your business?

Start with a free consultation. We'll review your current situation, scope the approach, and give you a realistic outcome estimate — no obligation, no generic pitch deck.

View the service page →
— Related Work
📄
Invoice Processing Automation
94% touchless — 28hrs/wk saved
💬
SaaS Support Chatbot
70% ticket volume reduction
🔷
Zoho CRM Implementation
Full Zoho People + CRM rollout
🤖
AI Workflow Automation
View the full service page
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6 months ago

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