Software vendors like to claim unified systems that act as a so-called single pane of glass for any given coding task, data function, or broader workflow. Agentic data retrieval company Infino hints at that vibe, promising a single retrieval layer for all agents.

In this context, a single retrieval layer means a unified (there’s that word) database system that lets all AI agents query all data from one place.

Formally launching its agent retrieval platform on Wednesday, Infino says it built the platform because agents have changed the data query paradigm and don’t query like humans. 

Infino CEO Ekechi Nwokah tells The New Stack that agents are the “largest new consumer of data since the web browser”, but he laments that they are still “being served with a fragmented stack built for a different era,” i.e., data warehouses for SQL, search engines for keywords, vector databases for semantic search, and ETL pipelines to keep them all in sync. 

“We’re collapsing that stack for agents,” Nwokah says. “Our approach is to put the data in Parquet in object storage and let agents search, rank, filter, join, aggregate, and reason over it directly. The result is one copy of the data that all agents read.”

As we know from database basics lesson #1, data stores have been traditionally optimized for a human or application that writes one query, waits, and reads the result. 

“An agent behaves quite differently,” Nwokah says. “It issues many small questions to answer one large one, often at the same time, and every result it receives consumes context and can add cost and latency to subsequent model calls.

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