Perforce Delphix AI Accelerates Secure Software Development with Synthetic Data Generation

Perforce's Delphix AI Boosts Software Development Speed and Security

Perforce Software has expanded its software testing and synthetic data capabilities by introducing AI-powered synthetic data generation through Delphix AI. This new feature is part of the Delphix DevOps Data Platform and aims to accelerate software development while enhancing data privacy and security.

Delphix AI Speeds Up Development with Embedded Language Model

Delphix AI incorporates a language model directly into the platform, enabling teams to automatically generate synthetic data throughout the development lifecycle. By combining data masking, delivery, and synthetic data generation in a single solution, and applying AI, Delphix offers an enterprise-grade toolset that supports DevOps acceleration, privacy compliance, and AI/ML model training.

Gartner research highlights a growing challenge: by 2027, 60% of data and analytics leaders may face critical issues managing synthetic data, which could affect AI governance, model accuracy, and compliance. Delphix AI addresses this risk by providing a built-in, optional AI model trained on Perforce’s extensive expertise in data privacy. This ensures synthetic data remains customizable, referentially intact, and suitable for compliant, high-fidelity test environments.

Key Benefits for IT and Development Teams

Delphix AI helps development, testing, and data science teams maintain constant access to compliant data. Its AI-generated synthetic data solution enables organizations to:

• Protect sensitive data by replacing it with synthetic alternatives that reflect realistic conditions for development and testing.
• Speed up data privacy compliance and security for analytics, AI training, and app development use cases.
• Support secure, compliant AI innovation without the need for extra data science resources, keeping all data within the company’s IT perimeter.

Perforce Intelligence powers this AI capability and will be central to upcoming synthetic data generation features. The platform runs a fully air-gapped, small language model on CPU only, allowing synthetic data to be created securely inside organizational boundaries.

Looking Ahead: More Intelligent Data Management Features

Future updates will introduce enhanced data compliance and test data management tools, such as unstructured data discovery and automated data delivery tailored for MLOps pipelines. These additions aim to further streamline data handling across software development and AI workflows.

For IT professionals interested in expanding their AI and data management skills, exploring targeted courses can provide practical knowledge to leverage these new technologies effectively. Relevant AI training resources can be found at Complete AI Training.