Building AI applications often requires searching through millions of documents, finding similar items in massive catalogs, or retrieving relevant context for your LLM.

Working with time series data often means wrestling with the same patterns over and over: calculating moving averages, detecting spikes, creating features for forecasting models.

When building machine learning models, most developers focus on model architectures and hyperparameter tuning.