Synthetic Data at Scale: Why K2View & Rocket Software Are Teaming

Mainframes. Synthetic data. AI-ready foundations. This was one of the most practical conversations we had at Gartner on The Ravit Show. I sat down with Ronen Schwartz, CEO at K2view and Michael Curry, President, Data Modernization, Rocket Software to talk about their partnership and why it matters right now.

Here is the reality.

A lot of enterprise data still lives in mainframes and core systems of record. At the same time, teams are racing to automate development, generate code with AI, and move faster than ever.

That creates a real gap.

We discussed:

-- Why customers building data products, test data management, and synthetic data pushed K2View and Rocket Software to collaborate

-- How modernization of legacy systems creates opportunities to generate and manage test data at scale

-- Why synthetic data is critical when you cannot simply move production data into lower environments

-- How teams can now generate code from a product story and also generate the data needed to test it

-- Why governance is the layer leaders must get right before scaling AI

One point stood out.

The technology leap toward AI is not the hardest part. Getting the data foundation, quality, and governance right is. If AI agents are going to act on enterprise data, that data must be trusted, protected, and consistent across systems of record.

Their advice to leaders was simple.

- Build AI-ready data environments.

- Partner with vendors who are deep in what they do.

- Carry your governance investments forward into your agentic AI strategy.

If you are modernizing mainframes, thinking about synthetic data, or preparing your enterprise for AI in production, this one is worth watching.

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