The pressure is on for development and testing teams to move faster, but there are roadblocks that get in the way. Teams often lack the data needed to develop and test new applications, features, and scenarios. Luckily, there's a way they can release the pressure: adopting synthetic data.
Synthetic data fills a crucial gap in the test data management puzzle — if you use it correctly. That’s why we launched new synthetic data capabilities in Perforce Delphix. In this webinar, Senior Product Manager Mayank Ahluwalia will show you how AI-first synthetic data generation works and why pairing it with data masking is the best way to get compliant data for all your use cases.
You will also learn:
- When to use synthetic data, masking, or both.
- Where to use synthetic to get the most value.
- How to ensure your synthetic data is high-quality and realistic.
- How Delphix helps you deliver fully compliant masked and synthetic data faster than any other toolset.
Ready to solve the gap in your test data strategy? Find out how to deliver the right data for development and testing without exposing sensitive information. Plus, you'll be among the first to see Delphix Synthetic Data in action in a live demo.
See for yourself how Perforce Delphix can help you automate compliant data for DevOps.
Presenters
Mayank Ahluwalia
Mayank Ahluwalia, Senior Product Manager for Perforce Delphix, has experience across data management, data compliance, systems architecture, machine learning, and AI. He has spent much of his career as a hands-on engineer building and operating real systems, which gives him a practical view of the challenges teams face implementing data and AI platforms.
At Perforce Delphix, he leads Synthetic Data and Compliance Services for Azure, helping engineering and data leaders tackle data bottlenecks with a privacy-first approach. He's also authored thought leadership on synthetic and AI, including the 2026 State of AI and Data Privacy Report, an article focused on data quality and AI on The New Stack, and a CIO Dive article on AI data privacy misconceptions.