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Case Study: How a Kent Engineering Firm Cut Quote Time by 85%
Case Studies7 January 20265 min read

Case Study: How a Kent Engineering Firm Cut Quote Time by 85%

SW

Sam Wilkinson

Founder, Kent AI Partners

Case Study: How a Kent Engineering Firm Cut Quote Time by 85%

The Problem

Kent precision engineering firm. 15 employees.

Their quoting process:

  • Receive RFQ (email or PDF)
  • Engineer reviews drawings manually
  • Calculates materials, time, complexity
  • Types quote into system
  • Sends proposal

Time per quote: 2-4 hours Quotes per week: 30+ Bottleneck: Everything waiting for one senior engineer

The Solution

AI-powered quoting assistant:

  • Extracts specs from drawings automatically
  • Pulls historical pricing for similar jobs
  • Generates draft quote in 10 minutes
  • Engineer reviews and approves

The Result

| Metric | Before | After | |--------|--------|-------| | Quote time | 2-4 hours | 30 minutes | | Win rate | Baseline | Up 15% | | Engineer time | Buried in quotes | Actually engineering |

The Cost

  • Total project: £20,000
  • Self-funded: £10,000 (Made Smarter matched the rest)
  • ROI: Under 3 months

What Made It Work

1. Clear Problem Definition

They knew exactly what was broken: quoting was the bottleneck. Not "we need AI" but "we need faster quotes."

2. Historical Data

They had 5 years of quotes in their system. The AI learned from their pricing history, not generic industry data.

3. Human In The Loop

The engineer still reviews every quote. AI does the heavy lifting, human does the judgment calls.

4. Proper Training

Two days of hands-on training. The team understood how to use it and when to override it.

This Is What Practical AI Looks Like

Not robots. Not job losses. Just working smarter.

The senior engineer now spends his time on complex quotes that actually need his expertise. The routine stuff handles itself.


Frequently Asked Questions

Can this work for my industry?

If you quote repeatedly and have historical data, probably yes. The specifics vary but the pattern is the same: extract, calculate, generate, review.

What if our quotes are very complex?

AI handles the routine complexity. Your experts handle the edge cases. Usually 80% of quotes can be automated, leaving humans to focus on the 20% that need real judgment.

How accurate is AI quoting?

In this case, AI draft accuracy was 85%+ out of the gate. After 3 months of learning, it's over 95%. The engineer still reviews everything, so nothing goes out wrong.


Kent AI Partners helps local manufacturers adopt AI and claim the funding they're entitled to.

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