Developer creates lightweight AI decision model running locally on laptop

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A developer built a small AI model designed to classify text inputs by selecting from lettered options rather than generating text. The model, based on Gemma 4 E2B with a 52 MB LoRA adapter, was trained on seven public datasets plus synthetic data using only a 24 GB MacBook. It processes approximately 85 milliseconds per decision and provides confidence scores to determine when to act or hand off to human agents. The system operates entirely locally without cloud APIs, addressing privacy considerations like India's DPDPA.

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