Abstract: For monitoring a building automation system, an artificial intelligence may be used to prioritize, diagnose, and/or provide cost estimates. For ease of interaction, a large language model (LLM) may be used. For operation of the LLM, a prompt requesting assistance is generated. The prompt includes context. Rather than providing the quite voluminous time series data, the context uses the faults and statistics. A processor adds this context to a prompt generated for input to the LLM. Based on the context and prompt, the LLM may rapidly and/or regularly provide accurate diagnosis, prioritization, and/or cost estimates for monitoring building automation. Due to the prompt and context, plain text information assisting in understanding and solving problems in building automation is output without a need for an expert.