Enterprise agentic AI with governance and developer tooling
robot_2 Agent execution

Scale, secure, and control multi-agent systems and operations

Run agent systems through a shared execution layer with guardrails, controls, and operational visibility.

  • Rest easy with reliability from durable execution 
  • Prevent malicious code execution
  • Control tasks with human oversight
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Key capabilities

Explore more agent execution capabilities

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Agent Harness

Agent Harness lets you invoke agents, see their actions, and guide execution with human approvals. 

  • Invoke agents via MCP‑enabled clients and APIs
  • Inspect planned vs. executed tool calls during runtime
  • Pause execution for human approval before sensitive actions
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Agent Runtime

Run agent code within a secure, production-ready runtime designed for long-running, governed workloads. 

  • Run agent processes with durable execution and state persistence
  • Isolate agent runs using sandboxed execution environments
  • Enforce identity, permissions, and policy checks at execution time
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Agent Development Kit (ADK)

Build and validate agents against real execution and governance constraints.

  • Build agents using open frameworks like LangGraph, CrewAI, and Flowise
  • Develop agents that connect to enterprise data through Teradata MCP
  • Test, iterate, and compose agents locally before deploying at scale
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Skills

Skills enable you to define reusable execution units across agent workflows. 

  • Define reusable behaviors as SKILL.md contracts with explicit intent and inputs.
  • Share skills as SKILL.md files across teams and users with clear scope and discoverability
  • Apply skills during execution with controlled tool visibility
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Observability

Capture and inspect execution time behavior across agents and workflows. 

  • Record every tool call, approval, and execution outcome
  • View end‑to‑end execution traces across agent workflows
  • Collect logs and metrics tied to runtime execution, not models
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Orchestration

Coordinate execution across multiple agents via MCP‑based orchestration.

  • Define execution sequences and dependencies across agents
  • Support parallel and conditional execution paths
  • Route outputs and context between agents via MCP‑mediated flows
Frequently asked questions

Teradata agent execution FAQ

Agent frameworks handle reasoning and planning. Agent execution governs how those decisions are executed in production, including isolation, approvals, orchestration, and observability without changing agent logic.

It’s a horizontal execution layer between agents and enterprise systems, providing runtime control, orchestration, and observability.

All tool calls pass through Teradata Enterprise MCP with authentication, role-based access, schema validation, and audit logging.

Execution is coordinated across agents through sequencing, parallelization, and context routing.

Execution telemetry includes traces, logs, tool calls, and performance metrics.

Agent execution should be used when agents act on systems, coordinate workflows, require approvals, or must be auditable.

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