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Posted by Phil Alsop on 30 January 2026 at 2:32 pm
  • news
Teradata has announced the launch of Enterprise AgentStack, an AI platform designed to support enterprise deployments in multi-agent and hybrid environments. The platform aims to help organisations move from pilot projects to full-scale AI implementations while realising potential returns on investment.


Enterprise AgentStack unifies the AI agent lifecycle through an open and connected architecture. This allows enterprises to deploy agents that operate across cloud and on-premises environments. Core components—Enterprise MCP, AgentBuilder, AgentEngine, and AgentOps—support secure data discovery, agent creation, deployment, monitoring, and governance.

Many enterprises face challenges in scaling AI agents due to complex data lifecycles. Integrating trusted data and applying context can slow innovation and increase operational costs. AgentBuilder is designed to streamline agent creation, supporting tools such as Karini.ai and pre-built agents for SQL optimisation, data science workflows, and system monitoring.

AgentEngine provides a deployment environment for agents across diverse infrastructure setups, enabling agents to interact with Teradata language capabilities and persistent memory. AgentOps offers a central interface for managing and monitoring agents, ensuring security, governance, and alignment with business objectives.

Teradata leverages its analytics expertise and enterprise-scale performance to support AI workloads. Built on an Autonomous AI + Knowledge Platform, the system enables enterprises to utilise existing data resources for agent operations.

Survey data highlights that AI governance is a common challenge. Enterprise AgentStack addresses this through integrated compliance, monitoring, and management features, helping organisations scale AI safely. According to Teradata, organisations with the right AI capabilities can achieve higher revenue growth compared with peers.

Enterprise AgentStack is designed to accelerate innovation and provide operational scalability, aiming to make AI deployment more manageable and reliable across enterprises.