Perforce Software has announced Delphix Synthetic Data, an AI-native solution designed to generate realistic, scenario-specific test data that maintains referential integrity across enterprise systems.
The launch addresses a bottleneck that has become more pressing as AI accelerates software delivery. Development and testing teams increasingly need high-quality test data at pace, particularly where production data is restricted, incomplete or simply does not cover the scenarios they need to test.
Delphix Synthetic Data automatically identifies data structures, relationships and business context across sources, removing much of the manual configuration that has long been associated with legacy synthetic data tools. Developers, testers and AI agents get immediate access to safe, high-quality data for new applications, features and agentic workflows.
Where existing tools fall short
Synthetic data has moved quickly from a niche capability to an essential part of enterprise software delivery. As organisations adopt AI-assisted and agentic development, synthetic data allows teams to generate data where production data does not exist, and to test edge cases that would otherwise go unexplored.
The difficulty has been the quality of what those tools produce. Legacy synthetic solutions demand heavy manual configuration and, according to Perforce’s own research, frequently fail to deliver the realism and referential integrity that enterprise teams require.
A 2026 Perforce survey of 518 enterprise technology leaders found a significant gap between what development teams need and what existing solutions deliver. Among those who had evaluated the available tools, only 34% said synthetic data provides referential integrity, and only 36% said it provides data realism. Both capabilities are essential for enterprise development, testing and agentic workflows.
The AI-native approach inverts the manual model. Delphix Synthetic Data uses AI to scan metadata and schemas automatically, and statistical analysis to understand data shape and distribution. Users describe the data they need in natural language and modify it the same way. Instead of waiting days or weeks for low-quality test data, developers, testers and agents can generate what they need in minutes.
Security by design
The solution carries a notable security dimension. Its built-in AI model stays within the customer’s own environment and analyses only metadata, meaning sensitive or customer data is never sent to the AI model. Customers can also bring their own preferred LLM, running within an environment they already trust and secure, with customer data masked before it reaches the model.
That combination matters for organisations in regulated sectors, where moving sensitive data outside the estate for testing purposes is rarely an option.
What it delivers
For enterprise teams, the solution targets three core outcomes: releasing software faster through easily generated test data; improving software quality with realistic, referentially intact data that reflects entity relationships, statistical shape and distribution; and ensuring compliance by keeping sensitive data out of non-production environments.
The core features include the bring-your-own-LLM model, masking of customer data into an LLM, and AI-assisted discovery and configuration.
“Organisations need realistic test data that can be generated quickly, scale across complex environments, and meet data privacy requirements,” said Jim Mercer, Program Vice President, Software Development, DevOps and DevSecOps at IDC. “Solutions like Delphix Synthetic Data that combine AI-driven automation with data quality and control are better positioned to address that need.”
“Your masked production data only tells you what already happened,” said Ilker Taskaya, Field CTO at Perforce Delphix. “Testing needs the cases that aren’t in production yet, and it needs them to hold together across every database and file format in the environment. Delphix Synthetic Data generates data in the shape teams specify, with referential integrity intact, so agentic development isn’t waiting on test data.”
Part of a wider platform
Delphix Synthetic Data sits within the Delphix DevOps Data Platform, which combines synthetic data generation with data masking, data delivery and centralised governance. Together these capabilities support a broader range of development and testing scenarios while maintaining consistent control over sensitive data.
Developers and AI agents can access data through the user interface, APIs and MCP-enabled workflows, allowing secure access wherever development takes place.
Further detail onDelphix Synthetic Data is available from Perforce, along with the full research report,The Synthetic Data Market Gap: Findings from our 2026 Survey.
