Teradata Corp. on Wednesday unveiled AgentBuilder, a platform designed to help enterprises develop and deploy artificial intelligence (AI) agents more efficiently.
AgentBuilder suite leverages open-source frameworks while integrating with Teradata’s existing AI and analytics infrastructure. The platform enables development teams to design, operationalize, and manage multi-agent systems that can access trusted enterprise data through Teradata Vantage’s hybrid cloud environment.
The announcement comes as organizations increasingly explore agentic AI applications but face significant implementation challenges. Obstacles include fragmented data sources that can lead to AI hallucinations, insufficient business context integration, performance issues with prompt-heavy workloads, and governance concerns around autonomous system deployment, according to Teradata.
“Despite growing interest in agentic AI, there are significant barriers to operationalizing autonomous agents,” the company said, pointing to data silos and lack of embedded business knowledge that has limited contextual relevance and reliability.
Beyond the development platform, Teradata is introducing pre-built Teradata Agents that incorporate specialized business logic and contextual knowledge to produce more relevant outputs that meet organizational goals.
The initial Teradata Agents lineup includes three specialized tools targeting key enterprise data operations. The SQL agent converts natural language queries into executable SQL code for Teradata data warehouses, automatically discovering schemas and optimizing query performance. Meanwhile, the data science agent generates complete machine learning pipelines from conversational requests, combining large language models with Teradata’s MCP tools to handle multi-step reasoning across ML workflows.
A third agent focuses on system management, providing continuous monitoring and maintenance of Teradata databases and infrastructure. The agent uses real-time telemetry to detect performance issues and system anomalies before they impact operations, enabling proactive maintenance across enterprise environments.
The platform builds on Teradata’s recently launched Model Context Protocol (MCP) Server, which provides semantic access to enterprise data across both cloud and on-premises environments.
Teradata Chief Product Officer Sumeet Arora positioned AgentBuilder as a bridge between AI experimentation and production deployment. “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,” Arora said.
He emphasized the platform’s hybrid infrastructure support as a key differentiator, noting that the solution delivers “trusted, transparent, and complete knowledge to power the next generation of AI.”
AgentBuilder will enter private preview later this year, with organizations able to request early access. Teradata plans to showcase the platform’s capabilities at its annual Teradata Possible conference, Oct. 6-8 in Los Angeles.
