In this interview, Shubhangi Dua, Podcast Host, Producer and B2B Tech Journalist at EM360Tech, speaks to Phillip Miller, AI Strategist and Director of Product Marketing at Progress Software, at Big Data LDN 2026 at Kensington Olympia, London.
At BDL, the most exciting thing on the floor for Miller was how all these enterprises are trying to solve these world challenges using AI. “We look at it with three ‘Cs’: Context, control and confidence.”
When asked about a data use that CEOs aren’t paying enough attention to, Miller says that enterprise data is often scattered through your business.
“The data is not connected necessarily from function to function, and people use other systems that aren’t compatible or don’t speak directly to their system.”
This is why, he says, it’s become more critical to bring that data together so the data can be connected to policies, governance, ontologies or taxonomies and everything that goes into turning that data into information.
However, the problem is, “a large percentage of people are taking a message from AI vendors as gospel, which is, ‘AI can do everything’,” the AI strategist tells Dua. The problem is that then people start to question why AI isn’t working.
It’s not working because the AI vendors won’t say the quiet part out loud, and that’s “we need a deterministic harness to go around our non-deterministic LLMs to deliver you consistent results, accurate results, timely results and complete understanding of how your business works.”
Watch Podcast with Progress: Why Enterprise RAG Systems Still Produce AI Hallucinations
Also Watch: Context, Cost, & AI: Strategies to Optimise Agent Performance & ROI
Visit progress.com.
Progress© Agentic RAG empowers enterprises to unlock the full value of unstructured data (documents, videos, etc.) by delivering trusted, context-rich answers with full source traceability. Its modular, no/low-code RAG pipeline indexes these files, then retrieves only the most relevant segments using advanced strategies and agentic orchestration. Every answer includes citations and retrieval logs, ensuring transparency and trust. With support for a wide array of LLMs, Progress Agentic RAG reduces hallucinations, accelerates AI adoption, and enables automation at scale. Organizations gain faster insights, improved decision-making, and measurable ROI without the complexity of building AI infrastructure from scratch.
