Adaptive ML enables enterprises to build and serve bespoke Large Language Models using advanced reinforcement learning techniques. The platform acts as an 'RL Ops' layer, allowing teams to fine-tune models via Direct Preference Optimization (DPO) and validate performance with automated AI judges. This approach significantly reduces hallucination rates and aligns model behavior with specific business logic better than standard prompting. This technology addresses critical bottlenecks in computational efficiency and data governance, supporting broader industrial automation.