
In this episode of Future Finance, host Paul Barnhurst and co-host Glenn Hopper are joined by guest Alex Brower, co-founder and CEO of QFlow.ai, to explore why forecasting problems often begin with the data layer. They discuss data plumbing, semantic alignment, Model Context Protocols (MCPs), vibe coding, and how finance and go-to-market teams can work from shared definitions to improve forecast quality and analysis.Alex Brower is the co-founder and CEO of QFlow.ai, helping finance and go-to-market teams connect data, improve forecast accuracy, and boost analyst productivity by up to five times. He previously led finance and marketing at high-growth tech firms like AppTelligent (acquired by VMware) and Cloud Academy (acquired by QA).In this episode, you will discover:How data hygiene and shared definitions improve forecastingWhy unified data alone does not solve business alignment issuesMCP vs semantic layers for reliable analysisThe risks of untested AI-generated analysisWhy AI cost and governance matterAlex explains how QFlow helps companies prepare data, run planning workflows, and turn analysis into board-ready stories.Follow Alex:Website: https://qflow.ai/LinkedIn: https://www.linkedin.com/in/alexbrower/Follow Glenn:LinkedIn: https://www.linkedin.com/in/gbhopperiiiFollow Paul:LinkedIn: https://www.linkedin.com/in/thefpandaguyFollow QFlow.ai:Website - https://bit.ly/4i1EkjgFuture Finance is sponsored by QFlow.ai, the strategic finance platform solving the toughest part of planning and analysis: B2B revenue. Align sales, marketing, and finance, speed up decision-making, and lock in accountability with QFlow.ai. Stay tuned for a deeper understanding of how AI is shaping the future of finance and what it means for businesses and individuals alike.In Today’s Episode:[00:00] – Introduction[02:15] – Data & Forecasting Challenges[06:43] – MCP vs Semantic Layers[09:55] – AI Coding Risks[15:52] – QFlow Data Preparation[18:10] – Planning & Business Insights[20:51] – Closing Thoughts
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