Context architecture is replacing RAG as agentic AI pushes enterprise retrieval to its limits
Redis built its name as the caching layer that kept web applications from collapsing under load. The problem it is targeting now has the same structure but is harder to solve: production AI agents failing not because the models are wrong, but because the data underneath them is scattered, stale and structured for humans rather than machines. Retrieval pipelines built for single queries cannot absorb the volume agents generate.The gap Redis is targeting is structural: agents make orders of magnit
Source — venturebeat
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Published: Mon, 18 May 2026 23:17:44 GMT
Category — AI
Region: venturebeat | Section: AI
Related: ai • venturebeat