Protegrity Launches Developer Edition for Data Protection in AI Workflows
Protegrity, a Stamford, Connecticut-based data security company, has launched Protegrity Developer Edition. This new tool, available on GitHub since June 30, 2023, aims to make data protection accessible and integrated into everyday development workflows.
The Protegrity Developer Edition uses machine learning classifiers and pattern-based techniques to identify sensitive data in logs, documents, and text. It offers a lightweight, containerized deployment with intuitive REST and Python APIs, removing barriers to evaluation and experimentation.
The tool includes data discovery features, sample applications, and APIs. It also provides semantic guardrails, offering a modular, real-time defense layer that blocks prompt injection, PII leakage, and off-topic responses before they execute. This enables developers, data scientists, ML engineers, and security teams to easily add data protection to generative AI (GenAI) and unstructured data workflows.
Tui Leauanae, Head of Developer Relations at Protegrity, stated that the goal is to align data protection with how teams build. The tool is tailored for privacy-critical GenAI use cases, such as protecting sensitive chatbot inputs, sanitizing prompts for large language models (LLMs), and preventing output leakage. It allows developers to discover and protect sensitive data in minutes using REST or Python, spanning prompts, training data, RAG retrieval, and model outputs.
Protegrity Developer Edition, the first enterprise-grade, governance-focused Python package for creating secure, well-governed data pipelines and AI workflows, is now available. It empowers developers to run everything on their own computers, test privacy features, and protect sensitive data without needing special licenses or complex setups.
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