Protegrity, a global data security leader, is releasing its free Developer Edition on GitHub to help developers, data scientists, ML engineers, and privacy/security engineers integrate data protection into GenAI and unstructured data workflows.
Based on an enterprise-grade, governance-driven Python package, Protegrity Developer Edition is designed to enable developers to build secure and trustworthy data engineering workflows—including AI pipelines and data preparation—ensuring a well-governed and successful AI experience, the company said.
Protegrity Developer Edition removes common barriers to evaluation and experimentation with a lightweight, containerized deployment and intuitive Representational State Transfer (REST) and Python APIs. Developers can quickly discover and protect sensitive data, advancing Protegrity’s mission to make enterprise-grade data protection accessible, the vendor said.
“We didn’t build this for the boardroom, we built it for the creators,” said Michael Howard, chief executive officer, Protegrity. “Protegrity Developer Edition is our way of saying, ‘Go ahead, break things, test boundaries and protect data like it matters, because it does.’ In a world where AI is outpacing policy and data drives both breakthroughs and breaches, privacy cannot be bolted on, it must be built in. That’s why we’re putting powerful tools directly into developers’ hands, with no gatekeepers and no waiting, making security a first-class citizen.”
Protegrity Developer Edition provides data discovery, sample applications, APIs, and semantic guardrails. Capabilities include:
- Discovery: Identify sensitive data in logs, documents, and text using a combination of machine learning classifiers and pattern-based techniques such as regular expressions.
- Find and protect APIs: Let developers discover and protect sensitive data in minutes using REST or Python, spanning prompts, training data, RAG retrieval, and model outputs.
- Semantic guardrails: Modular, real-time defense layer that inspects inputs, plans, tool calls, and outputs to block prompt injection, PII leakage, and off-topic responses before they execute.
Protegrity Developer Edition is tailored for privacy-critical GenAI use cases such as:
- Privacy in conversational AI: Sensitive chatbot inputs such as names, emails and IDs are protected before they reach generative AI models.
- Prompt sanitization for LLMs: Automated PII masking in prompts reduces risk during large language model prompt engineering and inference.
- Experimentation with Jupyter notebooks: Data scientists can prototype protection and discovery workflows directly in Jupyter notebooks for agile experimentation.
- Output redaction and leakage prevention: Detect and redact sensitive data in model outputs before returning them to end users.
- Responsible AI training data anonymization: Sensitive fields in training datasets are redacted to support compliant and ethical AI development.
Protegrity Developer Edition uses trusted technology to empower developers with the ability to run everything on their own computers and test privacy features without the need for special licenses or complex setups, the company said.
Protections can be controlled through a built-in policy with preconfigured users and user roles that provide the ability to tokenize, encrypt, mask, or pseudonymize with authorization depending on user's access levels.
Protegrity Developer Edition serves as a strategic on-ramp to Protegrity’s broader platform. Developers and security practitioners can rapidly iterate and test integration without enterprise IT teams, according to the vendor.
Protegrity Developer Edition is available now on GitHub and the Python module is also available through PyPI, complete with documentation, sample applications, and community support.
“Developers are at the forefront of innovation, and they need tools that don’t slow them down,” said Tui Leauanae, head of developer relations, Protegrity. “Our goal is to make data protection accessible, actionable and aligned with how modern teams build. Protegrity is providing a resource beyond privacy by offering the ability to be creative without compromise.”
For more information about this news, visit www.protegrity.com.