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AI Success Stories

While 80% of AI projects fail, these success stories demonstrate how evaluation-first methodology transforms business challenges into measurable results. Each project follows my proven approach: evaluate before implementing, connect AI to real business data, and deliver systems that work in production.

  • AI Maddy: Education AI that Saved Teachers 12 Hours Weekly

    Transformed classroom management through evaluation-first AI implementation that connected directly to school systems. Delivered 80% accuracy, sub-2-second responses, and 12 hours weekly time savings per teacher. Scaled successfully to 20+ schools by focusing on real-world needs over theoretical capabilities.

  • AI Coding Assistant: Enterprise Test Automation That Saved 20,000 Hours

    Transformed developer productivity by implementing evaluation-first AI that preserved code privacy while automating test creation. Improved code coverage by 30%, reclaimed 20,000 annual developer hours, and reduced production incidents by 25%. Successfully deployed across 30+ global offices with minimal training.

  • Banking AI Assistant: From 50% to 82% Accuracy in 8 Weeks

    Rescued a failing banking AI pilot through systematic evaluation that identified critical RAG pipeline issues. Improved accuracy from 50% to 82%, reduced hallucinations by 70%, and enabled expansion from a single pilot to multiple banking clients without disrupting existing systems.

  • AI Planning Suite: From Disjointed Ops to Scalable Precision

    Unified planning, auditing, and performance tracking into a single AI-powered system across agricultural facilities. Saved 300+ hours/month, eliminated planning errors, enabled 100% adoption, and boosted production efficiency by 3%—all without changing a single workflow.