Get AI-Ready: Announcing Monte Carlo’s Observability Agents and Unstructured Data Support

The two biggest data conferences of the summer are kicking off in June, and with all eyes on AI, data trust is at the forefront of the conversation.

Announcing Monte Carlo’s new AI-Ready Data capabilities, designed to ensure that what goes into your AI is just as reliable as what comes out. 

Get excited, here are the new capabilities launching:

• Observability Agents - Monte Carlo’s new AI-powered monitoring and troubleshooting agents make deploying intelligent data monitors and root-causing data quality issues fast and easy, going beyond simplistic recommendations that leverage signals across your data + AI estate. 

• Unstructured Data Monitoring – 90% of a company’s data is unstructured, yet for many organizations, its reliability remains a blind spot. Monte Carlo’s new support for unstructured data monitoring enables organizations to monitor for anomalies in their unstructured data assets across documents, chat logs, and more, all without needing to write a single line of SQL.

See these exciting new features in action at the summits:

👉 Monte Carlo at Snowflake Summit 

👉 Monte Carlo at Databricks Summit

BREAKING: This might be the most strategic AI data play we’ve seen all year!!!! Salesforce acquiring Informatica for $8B isn’t just a market shake-up—it’s a signal that the AI era will be won not just with models, but with clean, connected, and governed data.

Salesforce now gets direct access to Informatica’s strengths: deep data integration, metadata management, lineage, and governance. These are not just backend features—they're the foundation for deploying AI that’s context-aware, compliant, and enterprise-ready.

Here’s how this changes the game:
- For Salesforce: It builds a full-stack AI platform where data isn’t just powering analytics—it’s embedded into workflows, copilots, and decision-making.

- For enterprises: It offers a potentially unified solution to bridge siloed systems, reduce vendor sprawl, and trust their AI outcomes.

- For the AI ecosystem: It raises the bar. If your AI can’t connect to governed, real-time enterprise data, it may not be enterprise-grade.

- For other players: Ironically, this could also help platforms like Qlik, Snowflake, Databricks, and even Amazon Web Services (AWS) and Microsoft. Why? Because the spotlight is now on data infrastructure as the critical path to GenAI success.

- It validates the investments these platforms have been making—and forces them to sharpen their value propositions around openness, performance, and ecosystem extensibility.

This isn’t just a consolidation play. It’s a realignment of what the AI-first stack looks like. Less experimentation. More integration. Less demo. More deployment.

But here’s where I’m curious:
Does this acquisition accelerate the enterprise AI journey—or will the complexity of integration slow it down?

Are we moving toward platform dominance—or opening the door for smarter interoperability?

This moment is worth watching closely. Would love to hear where you stand.

🔍 Stay Ahead in AI & Data! Join 137K+ Data & AI professionals who stay updated with the latest trends, insights, and innovations.

📢 Want to sponsor or support this newsletter? Reach out and let's collaborate! 🚀v

Best,

Ravit Jain

Founder & Host of The Ravit Show