An autonomous, AI-native system and method for the orchestration and recovery of perishable resource capacity in service-based industries. The system bypasses legacy graphical user interfaces by utilizing API middleware to interface directly with existing scheduling databases. A Natural Language Processing (NLP) layer monitors unstructured communications to predict resource cancellations before they are formally logged. The system converts user profiles into high-dimensional vector embeddings to perform hyper-personalized matching. An autonomous agentic broker, utilizing a Large Language Model (LLM), conducts natural language negotiations, executes variable yield discounting based on real-time resource decay, and facilitates peer-to-peer slot swaps via double-atomic database updates, thereby eliminating human network latency.