February 2026

1. The Problem: Mobile Typing is Slow

  • The Challenge: Typing on mobile devices is error-prone and time-consuming.
  • The Need: Users need a smart assistant that anticipates their thoughts.
  • The Solution: SwiftPredict—a lightweight, low-latency prediction engine designed for the next generation of mobile apps.

2. The Algorithm: Smart Back-off

Our engine utilizes a Stupid Back-off Model to balance accuracy and speed: 1. Trigram Search: Looks at the last two words for specific context. 2. Bigram Fallback: If the context is new, it “backs off” to the last single word. 3. Unigram Fail-safe: Ensures a valid suggestion is always returned (e.g., “the”, “to”).

This approach ensures 100% coverage even for unseen phrases.

3. Performance Metrics

We optimized the model for the resource constraints of mobile/web environments: - Memory Footprint: Compressed raw corpora (500MB+) into a <10MB production database using frequency pruning. - Latency: Average prediction time is < 50ms. - Accuracy: Achieved a Top-3 Accuracy rate that rivals standard mobile keyboards.

4. The Application Interface

The Shiny App provides a clean, distraction-free interface: 1. Real-time Input: Accepts phrases of any length. 2. Instant Feedback: Displays the #1 prediction prominently. 3. Alternative Choices: Offers Rank #2 and #3 options for nuance.

Designed with a ‘Developer-First’ mindset using the Flatly theme.

5. Future Roadmap & Conclusion

SwiftPredict is ready for beta testing. - Next Steps: - Implement Part-of-Speech (POS) tagging for better grammar. - Add “User Adaptation” to learn from specific typing styles. - Why Hire Me? I built a full-stack data product that handles real-world constraints (memory/speed) effectively.