Tag: Agentic AI
Do Agents Still Need RAG with Million-Token Context Windows?
AI models can now take a million tokens in a single prompt, so it’s fair to ask why an agent still needs a layer that hunts down the few relevant passages before it answers. Narrowing first is cheaper and more accurate and it keeps you free to change AI vendors later.
What Is AI Token Economics - Tokenomics?
AI token economics connects model usage to the real cost of running an AI application. In this article, we’ll trace token consumption through a RAG pipeline and explore how teams can estimate and manage those costs.
MarkLogic Server 12.1: Agent Ready, Engineered for Greater Efficiency.
Discover the key improvements in Progress MarkLogic Server 12.1 that boost your AI readiness and offer more cost-effective strategies to scale your critical initiatives.
What is Multi-Hop Retrieval?
Multi-hop retrieval runs several search passes in sequence to answer questions whose supporting evidence sits in separate documents. This post reviews what it is and how Progress Agentic RAG integrates multi-hop retrieval into its architecture.
How Self-Hosted Agents Make Cloud MFT Work Behind the Firewall
Cloud-managed file transfer does not have to drag your private endpoints onto a cloud execution path like luggage through a busy airport. Where the agent sits changes everything, and no amount of console polish will change that for you.
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