AI-Powered Quality Control for Diamond Processing Unit

Project Overview

Ratna Diamond Industries, a prominent diamond processing unit in Surat handling 15,000+ stones monthly, was facing mounting pressure from international buyers over inconsistent grading. With 12 inspectors of varying experience levels, grading the same stone could yield different results depending on who inspected it. They needed AI to bring consistency and speed to their quality control process.

The Challenge

Grading Inconsistency

• 15-20% variance in grades assigned by different inspectors for the same stone
• Subjectivity in colour and clarity assessment causing buyer disputes
• No standardised process — each inspector relied on personal experience
• High-value stones sometimes undergraded, losing potential revenue

Operational Bottlenecks

• 80-100 stones per day per inspector — insufficient for peak season demand
• New inspector training requiring 2+ years before reliable grading
• Re-inspection requests consuming 20% of inspector capacity
• Manual logging of grades causing data entry errors

Our AI Solution

Phase 1: Data Collection & Model Training

• Partnered with GIA-certified graders to create gold-standard dataset
• Captured 50,000+ high-resolution images across 4C grading parameters
• Trained deep learning model on cut, colour, clarity, and carat assessments
• Achieved 98.5% agreement with expert human graders in validation testing

Phase 2: Hardware & Integration

• Designed custom imaging station with controlled LED lighting and calibrated cameras
• Built ergonomic workstation for seamless human-AI collaboration
• Integrated grading API with existing inventory management system
• Created real-time feedback loop for continuous model improvement

Phase 3: Deployment & Refinement

• Deployed 4 AI grading stations replacing traditional inspection setup
• Implemented human-in-the-loop validation for stones above $5,000
• Trained 8 operators on the new AI-assisted workflow
• Established weekly model performance reviews with expert graders

Results

Quality Improvement

• 98.5% grading consistency across all stations (up from 80-85%)
• 85% reduction in buyer disputes within 4 months
• Zero inspection-related shipment rejections since deployment
• Standardised grading regardless of the operator

Productivity Gains

• 3x throughput increase — 300+ stones per shift per station
• 70% faster individual stone grading time
• Freed up 4 senior inspectors for high-value stone specialist work
• New operators productive within 2 weeks instead of 2 years

Business Impact

• ₹25 lakhs annual savings from eliminated disputes and re-inspections
• Premium stone detection improved, capturing additional 8% revenue
• Peak season capacity met without temporary hiring
• International buyer confidence significantly strengthened

Client Testimonial

"The AI doesn't get tired, doesn't have off days, and doesn't play favourites. It's brought a level of consistency to our grading that we couldn't achieve with 30 years of training human inspectors. The ROI was clear within the first quarter."

Jayesh Sanghvi, Director, Ratna Diamond Industries