If I'm a customer at a bank or an insurance company or a pharmaceutical company, pick an industry or a vertical, what is a concrete example where what you do and what we do with Splunk Observability for AI can meaningfully change the game on the kind of value they harness from AI.

Absolutely.

I'll give you a concrete example, say, of a healthcare company.

They're building workflows to make critical decisions on, say, prior authorizations of expensive drugs.

They're using Gen AI to solve it, and they're building agents to automate this whole gnarly process.

And it's ripe for disruption, because these workflows are just filled with unstructured data, PDFs, documents.

And LLMs are, for the first time, we have technology that can make sense of it and take actions for it.

Walk us through the problem that you were looking to solve and walk us through why it's such a hard problem to solve.

If I'm a customer at a bank or an insurance company or a pharmaceutical company, pick an industry or a vertical, what is a concrete example where what you do and what we do with Splunk Observability for AI can meaningfully change the game on the kind of value they harness from AI.

Absolutely.

I'll give you a concrete example, say, of a healthcare company.

They're building workflows to make critical decisions on, say, prior authorizations of expensive drugs.

They're using Gen AI to solve it, and they're building agents to automate this whole gnarly process.

And it's ripe for disruption because these workflows are just filled with unstructured data, PDFs, documents.

And LLMs are, for the first time, we have technology that can make sense of it and take actions for it.

Um, walk us through the problem that you were looking to solve and walk us through why it's such a hard problem to solve.

Yeah

... which you did not test on.

In Galileo, we call them unknown unknowns.

So your agents will fail in nuanced ways where you didn't expect it.

That's where the discipline of catching these unknown unknowns and creating new evals and bringing them back to the offline testing environment, that's what creates the flywheel.

And there's many other elements to this flywheel where you have to collect the data and look at the traces and evaluate them, perhaps manually through a subject matter expert, but you can also use offline judges to evaluate them.

And these are workflows that we are seeing already, uh, i- in banks, in telecom companies, in consumer good, healthcare.

Yeah