How does real-world AI deliver value? The Ask Red Hat example

How does real-world AI deliver value? The Ask Red Hat example The technical engine: Granite and the guardrails of trust Measuring the unseen: The value of AI and Ask Red Hat Looking ahead: The roadmap to agentic AI About the author Matt Ruzicka More like this Why the future of AI depends on a portable, open PyTorch ecosystem Scaling Earth and space AI models with Red Hat AI Inference Server and Red Hat OpenShift AI Technically Speaking | Build a production-ready AI toolbox Technically Speaking | Platform engineering for AI agents Keep exploring Browse by channel Automation Artificial intelligence Open hybrid cloud Security Edge computing Infrastructure Applications Virtualization Share At Red Hat Summit 2025, we introduced Ask Red Hat , a conversational AI designed to be an intelligent front door for our customers. It began as a rapid 12-week build to prove that open source AI could transform the support experience. Today, Ask Red Hat has evolved from a proof of concept into a sophisticated production reality. As of late 2025, it has served over 50,000 unique users and handled more than 450,000 messages. It is no longer just a standalone tool but a cross-product orchestration layer, integrated directly into docs. redhat. com and new support case creation in the Red Hat Customer Portal. Ask Red Hat is delivering on its goal: Helping customers solve problems the very moment they arise. While much of the industry is still experimenting with models in isolation, Red Hat has operationalized the IBM Granite family to solve specific customer pain points. Our leadership in this space is defined by how we balance power with precision: The model: We use Granite-3. x 8B-Instruct variant for its high efficiency and precision in RAG (retrieval-augmented generation), with plans to migrate to Granite-4. x Small in the near future.