Jev and SemIf Reduce If-Then Logic Processing Costs by 99% and Double Accuracy

Dedicated decision (decider) models like Jev and SemIf are replacing complex generative reasoning used by existing AI models for simple if-then logic, showing breakthrough improvements in cost and performance. These technologies adopt a zero-token execution approach that returns typed decisions instead of generating text, maximizing efficiency in production environments.

Performance and Cost Improvements

Jev costs $0.042 per input token and $0 for output, making it 82x cheaper than Sonnet-class models. According to TypeSafe's workflow evaluation benchmarks, cost savings of 76–209x compared to frontier models were confirmed.

Accuracy and Validation Results

In a classification test of 98 validated production email threads, existing generative LLMs achieved 47% accuracy, while Jev achieved 80% and local SemIf achieved 82% accuracy. This represents approximately a 2x improvement in accuracy.

Polarization of the AI Economy

These changes suggest that the AI market is polarizing into 'development/experimentation' frontier models and 'production/cost-efficiency' specialized models. Once system implementation is complete, these specialized models are expected to contribute to margin expansion in harnesses when running large-scale workflows.