Memflex is a semantic memory layer for AI applications that matches incoming queries with previously answered requests. By reusing relevant responses, it aims to reduce redundant LLM calls, latency, and inference costs. Built for AI engineers, LLM developers, and agent builders who want to make AI applications more efficient while prioritizing response relevance and correctness.