H2O AI Super Agent™ is Added by AT&T to Power Enterprise Agentic AI

About this update from At&t Inc.

MOUNTAIN VIEW, Calif., July 14, 2026 --( BUSINESS WIRE )--H2O AI Super Agent™ is now being used by AT&T in its next phase of agentic AI initiatives and Ask AT&T , deploying autonomous agentic capabilities in workflows across customer experience, fraud prevention, field operations, enterprise research, and intelligent automation. The H2O AI Super Agent™ enables AT&T to orchestrate autonomous deep research agents, enterprise-grade retrieval-augmented generation (RAG) pipelines, predictive AI systems, and fine-tuned SLMs within a unified architecture designed for enterprise execution. This new integration builds on a long-standing relationship between AT&T and H2O.ai focused on operationalizing AI in production environments where scale, latency, governance, and cost efficiency matter. On an average day, AT&T processes tens of billions of tokens across enterprise AI workloads and has increasingly adopted fine-tuned small language models (SLMs) to improve accuracy, optimize latency at scale, and reduce costs by up to 90%. "At AT&T, we operate AI systems at enormous scale, processing about 45 billion tokens per day across complex environments, including customer and network operations, fraud prevention, and enterprise workflows," said Andy Markus, Chief Data Officer at AT&T. "As our AI initiatives expand, we need to reduce operational complexity, improve reasoning across separate systems, and deploy lower-latency, cost-efficient AI with enterprise-grade governance. "H2O AI Super Agent helps us orchestrate predictive AI and autonomous agents in a scalable architecture built for production. We see the opportunities to improve our employee and customer experiences, by deploying meaningful AI tools that drive business value and better serve our customers." — Andy Markus, Chief Data Officer at AT&T Moving Beyond Single Agents to Autonomous Enterprise Systems At the core of the H2O AI Super Agent is H2O.ai's convergence of agentic, generative, and predictive AI, combining large language and reasoning models with purpose-built, fine-tuned SLMs and predictive engines. This multi-agent architecture enables agents to reason over structured and unstructured data, make predictions, and execute decisions within end-to-end enterprise workflows. Rather than operating as a single executor, the H2O AI Super Agent acts as an orchestrator—decomposing high-level objectives such as enterprise research, analysis, synthesis, and decision support into structured sub-tasks, deploying agents in parallel, and dynamically adapting workflows based on context.

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