Teams often discover their model can't run efficiently on their target hardware after weeks of training. A pre-flight checker would save thousands in wasted cloud costs.
Build a web tool where users upload model architectures (PyTorch/TF) and select target hardware. Highlight ops that will underperform or fail, with optimization suggestions.
ML teams pay to avoid costly retraining and infrastructure mismatches. Could integrate with popular training platforms.
MVP: Rules engine for common GPU/TPU architectures with basic compatibility checks.
Risk: Hardware vendors may build this in-house.