It’s never been easier for an Ops team to build its own AI apps, scoring models, and workflows.
At Cockroach Labs, they didn’t wait for a vendor to build their AI-powered account prioritization and outbound system. Their GTM Ops team built it themselves.
And then things got interesting. 👀
More signals didn’t always mean better prioritization. More AI-generated scores didn’t necessarily give reps better answers. And as AI became easier to build with, new questions emerged around governance, data quality, costs, and keeping the stack under control.
In this AI IRL session, Jackson Mattox of Cockroach Labs joins Dom Freschi of Openprise and Matthew Volm of RevOps Co-op for a practical look inside how Cockroach Labs is putting AI to work across its GTM motion.
They’ll get into what the team has built, what they’ve learned along the way, and how they’re thinking about challenges like signal-to-noise, AI governance, data orchestration, and cost as their approach evolves.
🔑 Key Takeaways
A real-world look at how Cockroach Labs is using AI across its GTM motion
How to think about signal-to-noise as AI creates more scores and recommendations
What AI governance and control can look like as adoption scales
Lessons for building an AI-powered GTM stack without losing control of your data, tools, and costs
📣 Speakers
Jackson Mattox | Senior Manager, Marketing Operations, Cockroach Labs
Dom Freschi | Director, GTM Operations, Openprise
Moderator: Matthew Volm | CEO & Founder, RevOps Co-op
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