For enterprises pursuing private AI specific to their needs, Internalizer converts their text into a LoRA adapter, storing knowledge in model weights. It combines large-scale generalized learning with the specialized knowledge difficult tasks need, which neither plain LoRA training nor context distillation achieves alone. The frontier model stays frozen and a porting run fits to frontier models with far less GPU fine-tuning than traditional approaches. Adapters run in speed mode, dropping context to cut latency and cost, or accuracy mode, keeping both for higher accuracy.