Credit: VentureBeat, generated with MidJourney

Popular AI orchestration framework LlamaIndex has introduced Agent Document Workflow (ADW) a new architecture that the company says goes beyond retrieval-augmented generation (RAG) processes and increases agent productivity. 

As orchestration frameworks continue to improve, this method could offer organizations an option for enhancing agents’ decision-making capabilities. 

LlamaIndex says ADW can help agents manage “complex workflows beyond simple extraction or matching.”

Some agentic frameworks are based on RAG systems, which provide agents the information they need to complete tasks. However, this method does not allow agents to make decisions based on this information. 

LlamaIndex gave some real-world examples of how ADW would work well. For instance, in contract reviews, human analysts must extract key information, cross-reference regulatory requirements, identify potential risks and generate recommendations. When deployed in that workflow, AI agents would ideally follow the same pattern and make decisions based on the documents they read for contract review and knowledge from other documents. 

“ADW addresses these challenges by treating documents as part of broader business processes,” LlamaIndex said in a blog post. “An ADW system can maintain state across steps, apply business rules, coordinate different components and take actions based on document content — not just analyze it.”  

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