Redis debuts the much-needed memory layer for enterprise AI agents

Artificial intelligence agents have a memory problem and now Redis Inc., the database management startup, is trying to fix that with its new, real-time Context Engine.

As the company explains, it’s all about helping enterprise AI agents move beyond simply chatting to users and making them productive workers in their own right. Redis explained that there are three core tools behind the Context Engine, including the Redis Context Retriever, Redis Agent Memory and Redis Data Integration, with the latter made generally available starting today.

The three tools are designed to solve what Redis terms the “context problem” in enterprise AI, which causes autonomous systems to hallucinate and output incorrect information or results, or sometimes even stall from a lack of data. The company argues that the context problem is the result of a lack of memory, which causes problems when AI agents are asked to perform complex tasks. For instance, if an agent is trying to resolve a customer’s issue on the phone, it might need to pull data from the customer relationship management system, a shipping database and a PDF that outlines company policies.