Agents that get work done. Governance that lets them.
Make agents, orchestrate them across the tools you already run, and manage them with the same audit trail a regulator expects of a model. The H2O AI Super Agent is the orchestration layer underneath.
The H2O Agentic AI Platform is Make, Orchestrate, Manage: build agents, connect them over MCP and A2A, and govern them with logging, evaluation, and cost attribution.
The H2O AI Super Agent is the orchestration layer underneath, with nine agent types and 27 built-in tools.
Gartner predicts over 40% of agentic AI projects will be canceled by the end of 2027, citing cost, unclear value, and weak risk controls.
Existing agents co-exist with the Super Agent, so H2O.ai orchestrates what you already own rather than asking you to rebuild.
The Super Agent runs inside Ask AT&T and ranked #2 worldwide on the FutureX leaderboard in July 2026.
What is Agentic AI
Agentic AI is software that plans a goal, uses tools to act on it, and adapts as it goes.
Building the agent is the easy part. Agent projects break in four predictable places, and Gartner expects more than 40% of them to be canceled by 2027.
01UnmaintainableFrameworks hand you an agent for each workflow and a maintenance bill for each agent. Ten use cases become ten codebases and ten things to patch.
02UnaccountableAn agent took an action. Which tool, which data, which model, on whose authority? Without a trace, the first incident is the last one legal allows.
03UnbudgetedEvery step is a model call and every retry another. Agent spend arrives as a surprise, never attributed to a team, a task, or a decision.
04UnshippedThe demo worked on curated data. Production means messy documents, flaky tools, and a model risk team asking questions the framework cannot answer.
The record
9agent types in the H2O AI Super Agent
27built-in tools, plus MCP and A2A
#2worldwide on the FutureX leaderboard, July 2026
40%+of agentic projects canceled by 2027, Gartner
What the H2O Agentic AI Platform does
One orchestration layer for agents, not one framework per agent.
The H2O AI Super Agent makes, orchestrates, and manages agents from one place, with governance built in rather than bolted on.
Make agents, or use oursUse the built-in Super Agent, or build your own with Agents Builder and Flow. Nine agent types ship ready, from Deep Research to Code.
Orchestrate, don't rebuildConnect tools over MCP, let agents talk over A2A, and reach into ERP, CRM, data platforms, and the browser. Read the plan before it runs.
Manage every agent actionEvery step is logged and every cost attributed per user, team, and task. Evaluate agents in Eval Studio before they ever touch a customer.
Most organizations did not wait. They have agents in pilots, copilots from three vendors, and a data platform that just added its own. The H2O AI Super Agent does not ask you to start over. It governs and scales the agentic investments you already made, and adds the ones you are missing.
Co-existence by designCustom agents run alongside the built-in Super Agent, each with their own tools and configuration. Nothing gets thrown away.
Open protocolsMCP for tools, A2A for agents. Connect once, use everywhere. Nothing proprietary in the seams between systems.
Where it fits
The layer where agents run, across every capability.
The Super Agent sits above the predictive and generative lanes and reaches into both. It serves all four capabilities, not just this one. Highlighted are the Super Agent and the h2oGPTe platform it ships in.
Run it anywhere
You operate it, or H2O AI operates it for you.
Same platform either way: the same capabilities, the same governance, and the same audit trail. The choice stays open, so you can switch between them as the business changes, without rebuilding what runs on top.
AutoML automated the science. Agentic AI automates the thinking.
Each era automated something different, not more of the same. The agentic era is the one where the agent owns the goal, and H2O AI kept building through all three.
2015-2020AutoMLhow do I build the best model? Feature engineering, selection, tuning, AutoDoc. H2O-3 and Driverless AI.
2020-2024AutoAIhow do I get outcomes to decision-makers? Deployment, monitoring, governance, business-user access. H2O AI Cloud (now the H2O Sovereign AI Platform).
Gartner (25 June 2025) predicts more than 40% of agentic AI projects will be canceled by the end of 2027, citing cost, unclear business value, and inadequate risk controls. Building the agent is rarely the problem. Orchestration across tools, governance, cost attribution, and a trace of what the agent did are the hard parts.
Next step
Pick one workflow that touches three systems. Watch an agent run it.
We will connect the Super Agent to your tools over MCP, run the workflow with a human approval gate, and show you the audit trail afterwards.
Agents ground every plan in your documents with citations, then act. Retrieval becomes a step in reasoning, not a chat feature bolted on the side.
Predictive AI, from a sentenceThe Data Science Agent drives H2O Driverless AI, runs H2O-3, calls tabH2O, and hands models to MLOps. It operates the predictive engines, not replaces them.
Packaged vertical agentsAgents built for a specific job, such as FinCrime investigation, run on the same platform and are governed exactly the same way.
Built with youForward Deployed Engineers wire the first agents into your systems and hand over something your own team owns and runs.
Your existing agents, built on LangGraph, CrewAI, or the OpenAI Agents SDK, are hosted and governed alongside the Super Agent. An addition to your stack, not a migration off it.
The H2O AI Cloud for Government has achieved FedRAMP High Certification, delivering the highest standard of cloud security so federal agencies can harness predictive and generative AI without compromising data sovereignty or compliance.
BenchmarkFutureX leaderboardThe H2O AI Super Agent ranked #2 worldwide on the FutureX overall leaderboard in July 2026, a live benchmark of agents predicting real-world future events.Read the announcement
Agentic RAG grounds answers in your documents.
2024 onAgentic AIwhat should I build, and why? Autonomous planning, tool orchestration, adaptive iteration. The Super Agent.
2026Nine agent types, MCP and A2A, FutureX #2 worldwide.The Data Science Agent drives the predictive lane.
AI observability on the H2O AI Platform: explainability with AutoDoc, agent and RAG evaluation, drift and fairness monitoring, and one audit trail.
