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Agents are continuous, autonomous, and unforgiving. Without a trusted source of data and context in place, the simplest AI use cases require expensive workarounds, and the more ambitious ones aren't possible at all.
Agents consume data continuously, expect it to be consistent across every system, and amplify any inefficiency around them. Building real AI on top of infrastructure designed for human analytics means every initiative pays a tax in cost, in time, and in workarounds.
The distance between where you are now and where AI agents need you to be isn't cosmetic. Every quarter that goes by without closing it makes future AI initiatives more expensive to build, and the ones that don't get this right end up shelved instead of shipped.
You've built the foundation that lets AI agents work the way they're designed to: continuously, autonomously, at scale. But as agent traffic grows from hundreds of human queries per day to thousands, even the strongest positions face new demands.
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