MOUNTAIN VIEW, Calif.--(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. 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.
How AT&T Will Use the H2O AI Super Agent Across the Business
As part of the deployment, AT&T is using the H2O AI Super Agent to support workflows across customer experience, network operations, security, and risk management, including:
- Fraud prevention and financial crime detection, using predictive and agentic intelligence to identify anomalies and reduce risk
- Customer experience and field operations intelligence, leveraging fine-tuned language models to improve resolution quality, response speed, and operational efficiency
- Enterprise research, document intelligence, and content generation, enabling the agent-based RAG capability to “talk” to documents
- Advanced analysis and visualization of structured data, including tabular, spreadsheet-based, network, and tower datasets
- Expansion of the Ask AT&T platform, with new agent-powered capabilities and interoperable workflows across internal systems and APIs
Enterprise-Ready and Built for Regulated Environments
The H2O AI Super Agent is designed for enterprise production from the ground up, with embedded risk controls, audit trails, and governance. For regulated environments, H2O.ai supports sovereign AI deployments, including air-gapped and on-premises configurations, allowing organizations to deploy agentic AI within their own infrastructure while maintaining full control over data, models, and execution.
“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 built to support AT&T’s massive enterprise data ecosystem. Designed to help teams reuse, govern, and operationalize machine learning features across the enterprise, the platform addressed one of the most resource-intensive challenges in AI development: feature engineering.
Beyond enterprise AI deployments, the collaboration has also included joint AI-for-Good initiatives, such as flood prediction research with Argonne National Laboratory, validating that AI-driven models can replicate complex physics-based simulations and accelerate scientific discovery.
H2O.ai created the industry's trusted Sovereign AI Platform because organizations should own their AI: their agents, models, data, and results, run anywhere from cloud to air-gapped.
Super Agent orchestrates predictive, generative, and agentic AI in one system, with observability and governance, empowering regulated and public sector organizations to get value from AI. Moving from pilot to production takes expertise, from top-ranked data scientists, including Kaggle Grandmasters, to forward-deployed engineers embedded with customer teams.
Built on a decade of open source, H2O.ai is trusted by 20,000+ organizations, half the Fortune 500. AT&T, Commonwealth Bank of Australia, Wells Fargo, Bank of America, Workday, Progressive Insurance, and NIH rely on H2O.ai to cut cost and risk and own their AI future.
Through its AI for Good program, H2O.ai applies technology and investment to non-profits and academia solving hard problems in health, education, and the environment.
Learn more at h2o.ai.