Most enterprises hold massive volumes of logs, metrics, and sensor data, but lack the necessary infrastructure to extract value from them. While LLMs process discrete tokens in sequential context windows, machine data operates as a continuous time series. Several organisations, including Google, Amazon, Salesforce, IBM, and Splunk, have released various foundational models for machine data in the time series format. Just as large language models understand how to learn from natural language and provide relevant outputs, these models can interpret and understand time series data in a similar manner. Among these efforts, Splunk's approach offers a representative case study for how enterp