We're thrilled to announce a major breakthrough in our AI attention prediction technology. Our latest model training has achieved unprecedented accuracy levels, with validation error rates below 4.5% across all attention components.

🎯 Record-Breaking Performance Metrics

The latest training results from July 2025 demonstrate exceptional improvement:

• Overall Training Error: 3.85% MAE
• Overall Validation Error: 4.52% MAE
• Hold Component: 0.043 MAE (sustained attention prediction)
• Speed Component: 0.052 MAE (first fixation timing)
• Reach Component: 0.040 MAE (participant coverage)

📊 Comprehensive Training Dataset

These remarkable accuracy improvements are powered by our comprehensive training dataset:

• 33,998,738 Eye Fixations: Massive dataset for robust prediction accuracy
• 1,774,117 Eye-Tracking Tests: Extensive real-world validation data
• 12,053 Distinct Items: Comprehensive coverage across industries and design types
• Diverse Viewing Patterns: Unprecedented diversity in attention behaviors

🔬 Industry-Leading Accuracy

With error rates consistently below 5.5% across all attention components, our model now delivers:

• Best-in-class sustained attention prediction (Hold component)
• Exceptional immediate attention capture accuracy (Speed component)
• Outstanding participant coverage forecasting (Reach component)

💼 Real-World Impact for Businesses

This level of accuracy translates to more reliable design optimization decisions, reduced testing costs, and higher confidence in pre-launch design validation. Businesses can now trust our predictions for critical design decisions with research-grade confidence.

Experience the power of our enhanced accuracy for your design projects. Book a demo to see how these improvements can optimize your specific use cases.

We're excited to announce the launch of RealEye Attention Predictor, a groundbreaking AI technology that revolutionizes how businesses optimize their product designs. Built on 33,998,738 eye fixations from 1,774,117 eye-tracking tests across 12,053 distinct items, our attention prediction model delivers unprecedented accuracy in forecasting visual attention patterns.

🎯 Perfect for Product Design & Packaging

The Attention Predictor excels at Product Design optimization, helping brands create packaging that captures attention and drives sales. Whether you're designing consumer products, retail packaging, or marketing materials, our AI provides actionable insights to maximize visual impact.

🔬 Science-Backed Accuracy

Our model predicts four key attention metrics with exceptional precision:

• Hold (Fixation Duration): How long customers focus on specific design elements
• Speed (Time to First Fixation): How quickly key elements capture attention
• Reach (Coverage Ratio): What percentage of viewers notice important areas
• VAI (Visual Attention Index): Overall attention performance score

💡 Key Benefits for RealEye Customers

• Pre-test designs before expensive production runs
• Validate design decisions with objective data
• Optimize packaging for maximum shelf appeal
• Compare design alternatives with scientific precision
• Reduce design iterations and time-to-market

🚀 Available Now

The Attention Predictor is available as both a Python ML model for direct integration and a REST API for easy implementation. With Mean Absolute Error (MAE) as low as 0.04, it provides research-grade accuracy at commercial scale.

Ready to transform your product design process? Book a personalized demo to see how the Attention Predictor can optimize your specific use cases and deliver measurable ROI.