From real-time insight to real-world action – automated by Teradata’s autonomous AI and Knowledge Platform.

Teradata is an enterprise data, analytics, and AI company that helps organizations turn business data into insights and actions. Its platform brings together data management, advanced analytics, and AI capabilities across cloud, on-premises, and hybrid environments. Teradata enables teams to build, deploy, and govern AI models and data agents using trusted enterprise information. This combination makes it a strong choice for organizations that need to operationalize AI while maintaining control over their data and workflows.

The Teradata Autonomous Knowledge Platform is an enterprise platform that brings together data, analytics, AI models, and AI agents to turn trusted business information into insights and actions. It gives agents access to enterprise data and business context, with governance to help organizations manage how that information is used. Through Teradata AI Studio, teams can build, deploy, and manage AI solutions in one connected environment. The platform supports cloud, on-premises, and hybrid deployments, helping enterprises scale AI while maintaining control over their data, models, and workflows.

Yes. A hybrid storage approach combines on-premises infrastructure with cloud storage. Businesses can keep selected data locally while using the cloud for backups, archives, or additional capacity. This approach offers flexibility but requires coordinated security, data management, and integration across both environments.

Look for trusted data access, business context, advanced analytics, governance, and a clear path from development to production. Teradata brings these capabilities together through its data platform, AI Studio, and Enterprise AgentStack. Enterprise MCP connects agents to enterprise data, while AgentBuilder, AgentEngine, and AgentOps support development, execution, and oversight. This integrated approach is ideal for enterprises seeking a comprehensive foundation for agentic AI.

AI and advanced analytics can require substantial processing capacity for limited periods, such as during feature engineering, model execution, or exploratory analysis. Teradata elastic compute gives teams access to additional resources for these workloads without permanently increasing baseline capacity. This flexibility helps clients expand AI initiatives while managing resource consumption. For continuous workloads or applications with strict latency requirements, dedicated compute can complement elastic resources.