Oryn is a compact, low-latency decision model based on BERT Mini that performs classification by scoring dynamically supplied options at inference time rather than using a fixed output layer. At approximately 21 MB with 3 ms latency, it handles binary, multiclass, and ordinal tasks and was trained on phishing detection, reading comprehension, news classification, and sentiment analysis datasets. The model is optimized for local, CPU-friendly inference and works best on tasks similar to its training data.