H2O AI announced that AT&T has adopted H2O AI Super Agent™ for the next phase of its agentic AI strategy. The deployment also extends the capabilities of Ask AT&T by introducing autonomous AI. It supports 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 and enterprise-grade retrieval-augmented generation (RAG) pipelines. It also supports predictive AI systems and fine-tuned small language models within a unified enterprise architecture. Consequently, the company can support production-ready AI workloads while maintaining performance and governance.
The latest integration builds on the long-standing collaboration between AT&T and H2O.ai. Their partnership focuses on operationalizing AI for large-scale production environments where governance, latency, scalability, and cost optimization remain essential. Every day, AT&T processes tens of billions of AI tokens across enterprise workloads. Additionally, the company increasingly relies on fine-tuned small language models to improve accuracy, reduce latency, and lower operating 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
H2O AI Super Agent Expands Intelligent Enterprise Automation
The heart of the platform is H2O.ai’s single framework that brings together agentic AI, generative AI and predictive AI. Its architecture incorporates reasoning models, large language models, predictive engines and purpose-built small language models. Thus, autonomous agents are capable of analyzing both structured and unstructured information and supporting enterprise decision-making.
It is not a single AI executor, but rather an orchestration platform, the H2O AI Super Agent. It splits complex objectives into structured tasks, coordinates multiple agents at once, and continuously adapts workflows according to business context.
AT&T is implementing the platform for customer experience, network operations, security, enterprise research and risk management. The solution enables fraud prevention, financial crime detection, intelligent document analysis, content creation, advanced structured visualization of data and continuous expansion of the Ask AT&T platform through agent-driven workflows.
The H2O AI Super Agent also includes built-in governance, audit trails, and enterprise-grade security controls. It’s also designed for sovereign AI deployments, including on-premises and air-gapped environments. This allows organizations to maintain full control of data, AI models and execution in regulated industries.
“AT&T stands out as one of the most advanced enterprise AI organizations in the world – we are excited to be powering thousands of users and agents on Ask AT&T. H2O AI Super Agents are sophisticated coding agents with accurate tool calling, orchestrating deep research, reasoning, predictive intelligence, and purpose-built small language models. They are designed for traceable, high-fidelity execution across long-running business tasks on both private and public data.” Sri Ambati, Founder and CEO at H2O.ai
The collaboration also includes the co-development of the H2O AI Feature Store, originally created for AT&T’s enterprise data ecosystem. The platform helps organizations govern, reuse, and operationalize machine learning features more efficiently. In addition, both companies have collaborated on AI-for-Good initiatives, including flood prediction research with Argonne National Laboratory, demonstrating AI’s ability to accelerate scientific discovery through advanced predictive modeling.
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News Source: Businesswire.com
