All Case StudiesLogistics & Freight Transportation

AI Email Extraction Cuts Quote Response Time from Hours to Minutes

104 real RFQ emails processed with 88.5% pickup accuracy. Quote turnaround went from 2.8 hours to under 10 minutes on the first measured batch.

A mid-sized Indian logistics operator|December 2025

104

Emails Tested

99%

Processing Success

88.5%

Pickup Accuracy

<10 min

Quote Turnaround (was 2.8 hours)

The Challenge

A mid-sized Indian logistics operator faced a visibility problem that plagues freight companies globally:

✓Hundreds of RFQ emails daily - each in a different format (tables, conversational, mixed)
✓2.8 hour median response time - sales staff manually read and entered each email
✓No visibility into pending inquiries or response performance
✓Lost deals to faster competitors - first reasonable quote usually wins

The Solution

FasterQuotes deployed an AI extraction system using Google Gemini to automatically parse RFQ emails:

Email Ingestion: Connect to Gmail accounts receiving RFQ inquiries

AI Extraction: Gemini reads raw email text, extracts: pickup, drop, weight, vehicle type, quantity

Confidence Scoring: Each field gets HIGH/MEDIUM/LOW confidence rating

Human Review: Staff validate AI suggestions, make corrections if needed

Quote Generation: Structured data feeds directly into quotation workflow

Note: The AI only extracts from the inquiry - it never sees your pricing or quotation.

The Results

We tested 104 verified inquiry-quotation pairs from 12 unique sender domains:

88.5%

Pickup Accuracy

80.8%

Drop Accuracy

89.4%

Weight Accuracy

99%

Processing Success

✓Under 1 hour responses: went from 31.5% to 100%
✓Over 24 hour responses: went from 23.2% to 0%
✓Handles port names, CFS terminals, city aliases automatically
✓Works with KG, MT, tons, per-container weight formats

Key Insight: Most "errors" were naming/alias issues (BARODA vs VADODARA). With a simple alias table, accuracy improves to 95%+.

The Transformation

Before

×2.8 hour median response time
×23% of inquiries took 24+ hours
×Manual data entry from emails
×No visibility into performance

After

✓Quote turnaround under 10 minutes
✓100% of inquiries under 1 hour
✓AI extracts data automatically
✓Full visibility into every inquiry

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The Challenge

A mid-sized Indian logistics operator faced a visibility problem that plagues freight companies globally:

✓Hundreds of RFQ emails daily - each in a different format (tables, conversational, mixed)

✓2.8 hour median response time - sales staff manually read and entered each email

✓No visibility into pending inquiries or response performance

✓Lost deals to faster competitors - first reasonable quote usually wins

The Solution

FasterQuotes deployed an AI extraction system using Google Gemini to automatically parse RFQ emails:

Email Ingestion: Connect to Gmail accounts receiving RFQ inquiries

AI Extraction: Gemini reads raw email text, extracts: pickup, drop, weight, vehicle type, quantity

Confidence Scoring: Each field gets HIGH/MEDIUM/LOW confidence rating

Human Review: Staff validate AI suggestions, make corrections if needed

Quote Generation: Structured data feeds directly into quotation workflow

Note: The AI only extracts from the inquiry - it never sees your pricing or quotation.

The Results

We tested 104 verified inquiry-quotation pairs from 12 unique sender domains:

88.5%

Pickup Accuracy

80.8%

Drop Accuracy

89.4%

Weight Accuracy

99%

Processing Success

✓Under 1 hour responses: went from 31.5% to 100%

✓Over 24 hour responses: went from 23.2% to 0%

✓Handles port names, CFS terminals, city aliases automatically

✓Works with KG, MT, tons, per-container weight formats

Key Insight: Most "errors" were naming/alias issues (BARODA vs VADODARA). With a simple alias table, accuracy improves to 95%+.