Ingestion and the data foundation
Before AI can read your data, something has to collect, clean, and shape it. That is the foundation.
Ingestion is the work of getting data from where it lives into a place you can use. Sources are messy: databases, file shares, SaaS exports, event streams, and documents in a dozen formats. A pipeline pulls from each, on a schedule or in real time, and lands it somewhere consistent.
Landing raw is only the start. We model the data into clean tables with clear types, keys, and contracts, so downstream systems can trust the shape. Transformations are version-controlled and orchestrated, and every run is repeatable.
This is what retrieval and agents stand on. Embeddings, search, and models are only as good as the corpus underneath them. When the foundation is missing, we build it first: the pipelines, the storage, and the platform that keeps them running.