Teradata unveiled AgentBuilder, a powerful suite of tools designed to accelerate the creation and deployment of autonomous, context-aware AI agents. By leveraging open-source frameworks and harnessing the power of the Teradata AI and knowledge platform, AgentBuilder enables teams to quickly design, operationalize, and manage multi-agent systems. These systems draw insights from Teradata Vantage’s trusted data, advanced analytics, and hybrid infrastructure. Additionally, AgentBuilder introduces Teradata Agents pre-built, task-specific templates that accelerate implementation and deliver immediate impact for complex, domain-focused challenges.

The platform will enter private preview later this year, with a special showcase of its AI capabilities planned at Teradata Possible 2025, scheduled for October 6–8 in Los Angeles.

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While interest in agentic AI grows, organizations face challenges in operationalizing autonomous agents. Fragmented data can lead to hallucinations and unreliable results, lack of embedded business knowledge may reduce contextual relevance, prompt-driven workloads can cause performance bottlenecks and high costs, and insufficient governance increases deployment risks.

AgentBuilder addresses these obstacles by combining contextual knowledge, deep domain expertise, and scalable hybrid infrastructure. Organizations can now build and manage multiple autonomous agents across cloud and on-premises environments with enhanced security. Teradata Agents integrate business-specific logic and domain expertise, producing outputs that are more reliable and contextually relevant. Powered by Teradata’s knowledge platform, AI, analytics, and the newly launched Model Context Protocol (MCP) Server, AgentBuilder helps organizations move from experimentation to full-scale production, unlocking significant business value.

“AgentBuilder represents meaningful progress in advancing agentic AI for the autonomous enterprise,” said Sumeet Arora, Chief Product Officer at Teradata. “By combining the flexibility of open-source frameworks with Teradata’s AI and knowledge platform and our MCP Server, which provides deep semantic access to enterprise data, we’re helping organizations build intelligent agents that are not only autonomous and scalable, but also deeply aligned with their business goals, governance standards, and domain expertise.”

Arora added, “Add to that our seamless support across cloud and on-premises environments, and we’re delivering a level of flexibility, integration, and contextual intelligence that sets Teradata apart. This is not just about data it’s about delivering trusted, transparent, and complete knowledge to power the next generation of AI.”

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AgentBuilder supports popular open-source frameworks such as Flowise and CrewAI, with LangChain and LangGraph coming soon. The platform’s modular tools streamline workflows, memory management, reasoning, and coordination for autonomous systems, while Teradata’s enterprise-grade scalability and governance accelerate real-world AI adoption.

The included Teradata Agents cover high-value tasks such as churn analysis, system monitoring, and data science workflows. For instance:

  • Teradata SQL Agent translates natural language requests into optimized SQL queries and can integrate with multi-agent systems.
  • Teradata Data Science Agent builds fully executable ML pipelines from natural language, combining LLMs and MCP tools for reasoning, contextual understanding, and actionable insights.
  • Teradata Monitoring Agent continuously oversees databases and systems, proactively detecting anomalies and optimizing performance.

With AgentBuilder, Teradata empowers organizations to harness autonomous AI that is scalable, intelligent, and deeply aligned with business objectives.

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