Red Hat Launches AI Portfolio with Chatterbox Labs

Red Hat has announced it has acquired Chatterbox Labs, a pioneer in model-agnostic AI safety and generative AI (gen AI) guardrails. This acquisition adds critical “security for AI” capabilities to the Red Hat AI portfolio, strengthening the company’s efforts to deliver a comprehensive, open source enterprise AI platform built for the hybrid cloud. This announcement builds on a year of rapid innovation for Red Hat AI, following the introduction of Red Hat AI Inference Server and the launch of Red Hat AI 3. Customers around the world and across industries are adopting Red Hat AI to drive innovation through generative, predictive and agentic AI applications. As enterprises move from experimentation to production, they face a complex challenge: deploying models that are not only powerful but also demonstrable, trustworthy and safe. Safety and guardrail capabilities are table stakes for modern machine learning operations (MLOps). This focus on security and trust reflects Red Hat and IBM’s commitment to helping clients adopt a security-first mindset as they scale AI responsibly across hybrid cloud environments. The integration of Chatterbox Labs’ technology creates a unified platform where safety is built in, strengthening Red Hat’s ability to enable production AI workloads with any model, on any accelerator, anywhere. Founded in 2011, Chatterbox Labs brings critical technology and expertise in AI safety and transparency. Their experience in quantitative AI risk has been lauded by global independent think tanks and policymakers, and this acquisition brings key machine learning technology to Red Hat. Chatterbox Labs delivers automated, customized AI security and safety testing capabilities, providing the factual risk metrics that enterprise leaders need to approve the deployment of AI to production. The technology offers a robust, model-agnostic approach to validating data and models through:

• AIMI for gen AI: Delivering independent quantitative risk metrics for Large Language Models (LLMs).
• AIMI for predictive AI: Validating any AI architecture across key pillars, including robustness, fairness and explainability.
• Guardrails: Pinpointing and remedying insecure, toxic, or biased prompts before putting models into production.

  This acquisition aligns with Red Hat’s vision to support diverse models and deployment targets across the hybrid cloud. It also complements the forward-looking capabilities introduced in Red Hat AI 3, specifically for agentic AI and Model Context Protocol (MCP). As enterprises adopt agentic AI, trusted and secure models become even more critical, given the complex, autonomous role of AI agents and their potential impact on core business systems. Chatterbox Labs has conducted investigative work into holistic agentic security, including monitoring agent responses and detecting MCP server action triggers. This work aligns with Red Hat’s roadmap for the Llama Stack and MCP support, positioning Red Hat to secure the next generation of intelligent, automated workloads on a trusted, enterprise-ready foundation. By combining Red Hat’s MLOps capabilities with guardrail capabilities from Chatterbox Labs, Red Hat will enable organizations to operationalize their AI investments with greater confidence.