Agentic AI promises transformative autonomy, yet enterprises face critical challenges that must be addressed before scaling adoption.
AI agents are only as reliable as the data they consume. Incomplete, inconsistent, or siloed datasets lead to hallucinations, flawed reasoning, and unreliable outputs. Without unified, high-quality data pipelines, agentic systems risk becoming liabilities rather than assets.
Generic intelligence isn’t enough. Agents must be infused with deep domain expertise and contextual understanding to deliver recommendations that align with real business goals. Without this, outputs remain disconnected from operational realities and strategic intent.
Natural language interfaces unlock new possibilities—but also introduce a surge in tactical workloads. The autonomous nature of agentic AI can overwhelm traditional infrastructure, driving up compute costs and straining orchestration tools not built for prompt-driven execution.
Early-stage agentic tools often lack enterprise-grade guardrails. Without robust auditability, policy enforcement, and access controls, organizations face heightened risks in compliance, data leakage, and unauthorized actions—making governance a non-negotiable foundation for deployment.
To overcome the limitations of early-stage agentic AI, Teradata delivers a comprehensive solution that combines Teradata AgentBuilder with its industry-leading data and analytics tools.
Teradata AgentBuilder lets enterprises quickly build, deploy, and manage autonomous AI agents with contextual knowledge and domain expertise, leveraging trusted data, advanced analytics, and hybrid infrastructure from Teradata Vantage.
AgentBuilder integrates business context and domain-specific logic directly into agent behavior, ensuring outputs are relevant, trustworthy, and aligned with enterprise goals.
Agents operate securely and autonomously across cloud and on-premises environments, providing seamless integration for existing Teradata customers.
AgentBuilder supports popular frameworks like Flowise and CrewAI, with LangChain and LangGraph coming soon, enabling flexible, modular agent workflows, memory, and reasoning.
Built on Teradata’s comprehensive knowledge platform and Model Context Protocol (MCP) Server, AgentBuilder delivers deep semantic access to enterprise data, curated prompts, and secure, scalable infrastructure for agentic AI.
Pre-built templates for tasks like churn analysis and system monitoring speed up adoption and deliver fast results. Teradata’s AI agents make it easy: the SQL Agent turns natural language into optimized queries, the Data Science Agent builds executable ML workflows, and the Monitoring Agent keeps systems healthy and high-performing.
Teradata Agents are designed to learn and evolve, delivering explainable, business-aligned outcomes and operating autonomously across business functions.
We enable expert agents enriched with industry context and enterprise-wide intelligence to drive more autonomous, informed decision-making—transforming workflows, accelerating decisions, and unlocking new business value across marketing, sales, service, and risk management.
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