ABET approved AI/ML criteria in October 2025. Your next accreditation visit will ask about it.
AI literacy aligned with ABET 2025-2026 criteria, from generative design to smart manufacturing. Deployed across ME, EE, CE, and IE departments in weeks by engineers who build with these tools.
The Challenges
What Engineering Schools face today
Generative Design Without Judgment
AI-assisted CAD tools generate hundreds of design alternatives. Graduates who accept optimized outputs without evaluating safety constraints, manufacturing feasibility, or failure modes create engineering risk that conventional review processes were not built to catch.
AI Simulations Trade Accuracy for Speed
AI surrogate models run 1000x faster than traditional FEA/CFD, but the accuracy trade-offs are non-obvious. Graduates who do not understand when surrogates are appropriate make structural and thermal decisions on flawed simulations.
QC Automation Has Blind Spots
Computer vision inspection catches defects humans miss, and misses defects humans catch. Graduates need practical experience with AI inspection failure modes, calibration drift, and integration with existing QA processes before they manage a production line.
Industry 4.0 Requires AI-Literate Engineers
Smart manufacturing employers expect graduates who understand predictive maintenance, process optimization, and digital twin technologies. Programs that teach these as theory, without AI context, graduate engineers one toolset behind.
Solutions
How we solve each challenge
Solution
AI in Design Automation
Modules on AI-assisted design tools, from generative design principles to evaluation of AI-generated engineering solutions. Students learn to specify constraints, interpret optimization results, and validate AI designs against safety and performance requirements.
Solution
AI-Powered Simulation
Practical curriculum on AI surrogate models and their role in engineering simulation, covering model fidelity, validation methods, and appropriate use cases. Developed by engineers with experience in computational mechanics and AI/ML.
Solution
AI Quality Control
Hands-on modules on AI inspection systems, from computer vision defect detection to statistical process control with ML. Students work through quality scenarios drawn from manufacturing environments.
Solution
AI in Manufacturing
Industry-focused modules on AI in manufacturing operations, covering predictive maintenance, process optimization, and digital twin technologies. Built by engineers with smart manufacturing deployment experience.
Platform Preview
See it in action
Course Builder
Assessment Engine
Analytics Dashboard
Accreditation & Compliance
Built for regulatory confidence
ABET
2025-2026 AI/ML criteria alignment
Directly aligned with ABET's October 2025 AI/ML program criteria. Platform analytics provide the student outcome data ABET requires for continuous improvement reporting, ready for your next self-study without manual data assembly.
Case Study
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