Uploaded July 2026 | Updated September 2026, 2 weeks ago
Host: Cedric Clyburn
Guest: Roberto Carratalá
Producer: Rohan Venkatram
Cedric is joined by Roberto Carratalá, Principal AI Platform Architect within Red Hat’s AI Business Unit Customer Adoption and Innovation team.
Roberto specializes in container orchestration platforms—including Red Hat OpenShift and Kubernetes—alongside AI/ML, DevSecOps and CI/CD. With more than 10 years of experience across system administration, cloud infrastructure and artificial intelligence, Roberto also holds MSc degrees in Telecommunications Engineering and AI/ML.
In this episode, Cedric and Roberto explore Enterprise AgentOps: the platforms, processes and controls organizations need to move custom AI agents from early prototypes into secure, governed and observable production environments.
🎥 Interactive Demo Featured—follow along:
Enterprise AgentOps – Operationalizing AI Agents on Red Hat AI
redhat.com/en/interactive-demo/enterprise-agentops-operationalizing-ai-agents-red-hat-ai
🌐 Explore more demos at:
iredhat.com/en/interactive-experiences
👉 What you’ll see in this episode:
🤖 Enterprise AgentOps
Explore the end-to-end workflow required to deploy, register, manage and monitor enterprise AI agents.
🏦 Multi-agent workflows
See how specialized AI agents can collaborate across a banking workflow using LangChain.
🚀 Prototype-to-production deployment
Learn how Red Hat AI helps teams securely move custom agents from experimentation into enterprise environments.
🪪 Cryptographic agent identities
Discover how agents can be registered with verifiable identities to strengthen security, governance and accountability.
📊 Centralized agent management
Monitor agent status, endpoints and compliance from a unified operational view.
🧠 Models as a Service
See how organizations can centralize model access and consistently manage, deploy and scale models across teams.
🔍 Tracing and observability
Follow agent actions and model activity using MLflow, OpenTelemetry and the Red Hat OpenShift AI dashboard.
🛡️ Guardrails and content safety
Explore how safety controls help protect users, manage risk and support enterprise compliance requirements.
🔐 Zero-trust workload identity
See how real-time identity verification and secure backend analysis safeguard interactions across the agent workflow.
Whether you are experimenting with agentic AI or preparing to operate agents at enterprise scale, this episode shows what it takes to make AI agents trusted, observable and production-ready.
Subscribe to Red Hat Livestreaming for more technical demos, expert conversations and practical deep dives into enterprise open source technologies.
#RedHat #RedHatAI #AgenticAI #AIAgents #AgentOps #OpenShiftAI #OpenShift #ArtificialIntelligence #MachineLearning #MLOps #DevSecOps #ZeroTrust
Host: Cedric Clyburn
Guest: Roberto Carratalá
Producer: Rohan Venkatram
Cedric is joined by Roberto Carratalá, Principal AI Platform Architect within Red Hat’s AI Business Unit Customer Adoption and Innovation team.
Roberto specializes in container orchestration platforms—including Red Hat OpenShift and Kubernetes—alongside AI/ML, DevSecOps and CI/CD. With more than 10 years of experience across system administration, cloud infrastructure and artificial intelligence, Roberto also holds MSc degrees in Telecommunications Engineering and AI/ML.
In this episode, Cedric and Roberto explore Enterprise AgentOps: the platforms, processes and controls organizations need to move custom AI agents from early prototypes into secure, governed and observable production environments.
🎥 Interactive Demo Featured—follow along:
Enterprise AgentOps – Operationalizing AI Agents on Red Hat AI
redhat.com/en/interactive-demo/enterprise-agentops-operationalizing-ai-agents-red-hat-ai
🌐 Explore more demos at:
iredhat.com/en/interactive-experiences
👉 What you’ll see in this episode:
🤖 Enterprise AgentOps
Explore the end-to-end workflow required to deploy, register, manage and monitor enterprise AI agents.
🏦 Multi-agent workflows
See how specialized AI agents can collaborate across a banking workflow using LangChain.
🚀 Prototype-to-production deployment
Learn how Red Hat AI helps teams securely move custom agents from experimentation into enterprise environments.
🪪 Cryptographic agent identities
Discover how agents can be registered with verifiable identities to strengthen security, governance and accountability.
📊 Centralized agent management
Monitor agent status, endpoints and compliance from a unified operational view.
🧠 Models as a Service
See how organizations can centralize model access and consistently manage, deploy and scale models across teams.
🔍 Tracing and observability
Follow agent actions and model activity using MLflow, OpenTelemetry and the Red Hat OpenShift AI dashboard.
🛡️ Guardrails and content safety
Explore how safety controls help protect users, manage risk and support enterprise compliance requirements.
🔐 Zero-trust workload identity
See how real-time identity verification and secure backend analysis safeguard interactions across the agent workflow.
Whether you are experimenting with agentic AI or preparing to operate agents at enterprise scale, this episode shows what it takes to make AI agents trusted, observable and production-ready.
Subscribe to Red Hat Livestreaming for more technical demos, expert conversations and practical deep dives into enterprise open source technologies.
#RedHat #RedHatAI #AgenticAI #AIAgents #AgentOps #OpenShiftAI #OpenShift #ArtificialIntelligence #MachineLearning #MLOps #DevSecOps #ZeroTrust
