Teams often struggle with scattered prompts, inefficient iteration, and difficulty tracking performance improvements. LLM-Evalkit is an open-source application designed to bring structure to this process. It's a lightweight framework built on Vertex AI SDKs using Google Cloud. LLM-Evalkit centralizes and streamlines prompt engineering for more effective iteration. Currently, prompt management on Google Cloud is fragmented, leading to duplicated effort and inconsistent results. LLM-Evalkit abstracts these tools into a single, cohesive application for creation, testing, versioning, and benchmarking. This allows for better tracking of prompt history and performance, creating a reliable system of record. It shifts prompt iteration from subjective "feel" to systematic, data-driven measurement. Teams define specific problems, gather relevant datasets, and build concrete measurements for objective scoring. LLM-Evalkit also offers a no-code, user-friendly interface to make prompt engineering accessible to non-developers. This democratizes the process, allowing faster iteration and better collaboration. It helps teams move from ad-hoc experimentation to a structured and efficient workflow.