Product demo. 
3 Steps to AI-Ready Data 
What is a data mesh--and how not to mesh it up 
The ULTIMATE Guide To Data Lineage Monte Carlo is on a mission to accelerate the adoption of reliable data+AI
400+ Enterprise Customers
1,000 Incidents Resolved Daily
10M Tables Monitored
“Data observability has really shown its value for us — on one hand, scaling our products while on the other, keeping them healthy and keeping oversight.”
"Now we've got this extra level of insight...Monte Carlo helps us see these issues, which we did not previously have a way to easily visualize.”
“Even if you have access to all of the information in your entire data ecosystem, if you can’t trust the data, then it’s no good. For us, that’s where the data observability platform Monte Carlo comes in.”
Deliver on the promise of data + AI
In 2025, 100 percent of data leaders feel pressure to build GenAI, but only 68 percent don’t believe they’re AI-ready.
The culprit? Data downtime. Plaguing even some of the most data-driven enterprises, data downtime – when data is missing, inaccurate, or otherwise unreliable. While great tools existed to identify and resolve infrastructure issues, there was no easy way to guarantee the trust of data and AI pipelines.
With the proliferation of AI, the data estate has changed but the way we solve for data quality hasn’t. Until now.
AI + data observability, an industry-defining approach to finding and fixing data issues at scale. AI-ready starts with trusted data. Trusted data starts with Monte Carlo.
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