お知らせ • Jan 27
Teradata Unveils Enterprise Agentstack to Accelerate Agentic Ai
Teradata announced Enterprise AgentStack, designed to help enterprises to move from isolated pilots to production-grade autonomy quickly, even across multi-agent and hybrid environments. Product Description: Teradata Enterprise AgentStack is an open and connected stack that unifies the AI agent lifecycle to deliver production-ready agents with context and interoperability across hybrid environments. It includes Enterprise MCP for secure data discovery and system integration, AgentBuilder for creation, AgentEngine for deployment, and AgentOps for governance. Key Capabilities: Build intelligent agents that can find and use enterprise data, alongside context and reasoning, for autonomous outcomes. Enable secure, scalable interaction between agents and enterprise knowledge, with enterprise-grade analytics. Deploy, monitor and manage agents with security and governance across cloud and on-prem environments. Enterprises face a critical gap between agent experimentation and scaled deployment as leadership demands measurable ROI. The primary barrier is lifecycle complexity--finding and integrating trusted data, applying enterprise knowledge and context, enforcing governance, and maintaining compliance across hybrid environments. Without addressing these challenges, organizations risk stalled innovation and rising operational costs. Supporting stat: AI future-built organizations--those with the right capabilities to drive innovation and reinvention with AI--ach achieve 5x the revenue increases compared to their peers. (BCG, 2025) And because Teradata customers have mission-critical data already in systems--a gold mine ready for agents to find, use, and act on-- they gain a shortcut that helps turn agentic AI from inspiration into reality. What does Teradata Enterprise AgentStack Do? Build Agents Market challenges: Organizations struggle to securely integrate trusted data and inject context into agent thinking. Limited tooling and complex data requirements make moving from prototype to production slow and costly. Enterprise AgentStack includes two components to simplify and accelerate the building process: AgentBuilder: A tool for building intelligent agents faster, using integrated no-code and pro-code frameworks. In alignment with Teradata's open and connected strategy, options include Karini.ai, LangGraph, CrewAI, and Flowise. Agents access Teradata's context intelligence--industry data models, frameworks, and expert prompts--combined with tools from cloud service providers, NVIDIA, and open LLM APIs. Pre-built agents include Customer Lifetime Value, SQL optimization, data science workflows, and system monitoring. Supporting Quote: "Our collaboration with Teradata on Enterprise AgentStack accelerates the shift toward truly autonomous enterprises. By pairing Teradata's analytic performance and trusted data foundation with no-code agentic AI platform, organizations can transform static data into dynamic, intelligent workflows. Together, the company's enabling enterprises to scale agentic AI with confidence and deliver measurable impact faster. Enterprise MCP: A curated set of tools, prompts, and resources that provide enterprise-grade quality, security, and deep integration with Teradata platform capabilities. It provides ready-to-use components for discovering, orchestrating, and integrating mission-critical Teradata data into agent workflows--enabling fast, secure, context-rich interactions between AI models and Teradata's analytics and AI platform. Agentic actions include querying structured and unstructured data, advanced analytics, document extraction, semantic search, RAG-grounded responses, metadata discovery, and SQL generation and optimization. Deploy Agents Market challenges: Creating secure, scalable runtime environments that enforce permissions and guardrails is hard. Packaging agents with the necessary tools, models, and memory adds even more complexity, slowing the path to production. Enterprise AgentStack addresses these deployment challenges across the cloud and on-premises: New, AgentEngine: A secure, scalable execution environment for deploying AI agents across hybrid infrastructures. It supports single agents, multi-agent systems, and custom workflows from any agentic framework--en enabling agents to run together seamlessly while sharing memory, data structures, and execution workflows. Agents access Teradata LLM APIs and MCP tools for language capabilities, while persistent memory using structured and unstructured data enables context capabilities, while persistent memory using structure and unstructured data enables environment.