Data Strategy and Engineering for Agentic Workflows

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PwC surveyed 4,454 CEOs across 95 countries. 56% reported that AI has delivered zero financial benefit to their organization despite broad adoption. The primary reason: clean data.

If your marketing team is under pressure to integrate AI while nobody has sorted out what data feeds into these tools (and how) or how to measure what comes out, you’re in the same position as most companies.

Ray Grieselhuber founded DemandSphere (Y Combinator Summer 2010) and has spent 18 years building enterprise data infrastructure that connects search, LLM, and AI surfaces into a single analytics pipeline. He’s presented this work at brightonSEO, SMX Advanced, and FOUND Conference Tokyo.

Here is what we’re going to talk about: the data and retrieval layer underneath your AI tools determines whether those tools produce consistent, actionable output, and most marketing teams haven’t built it yet.

Next Wednesday, April 15, Ray is coming to MKE DMC to walk through data strategy and engineering for agentic workflows. The session is designed for marketers, not data engineers. If you want a practical framework for connecting AI tools to the data that makes them reliable, this is worth your Wednesday evening.

– MKE DMC, 318 N Milwaukee St
– Networking and happy hour at 5pm
– Ray talks at 6:15pm
– Wrap at 7:30pm