This enhancement to Teradata’s CX offerings will embed agents throughout the entire process — from constructing data products to detecting signals, interpreting context, and activating autonomous responses across hybrid infrastructure.
Teradata has announced the launch of Autonomous Customer Intelligence, a software and services offering designed to transform raw data and customer signals into context-aware, real-time actions at scale.
This enhancement to Teradata’s customer experience (CX) offerings will embed agents throughout the entire process — from constructing data products to detecting signals, interpreting context, and activating autonomous responses across hybrid infrastructure.
Critically, these agents will be powered by four decades of Teradata IP and contextual knowledge from solving mission-critical, industry-specific data challenges.
By using agents to eliminate friction in applying this proven expertise, Teradata supports customers’ efforts to achieve faster AI ROI while delivering enterprise-grade Autonomous Customer Intelligence.
To help customers achieve this vision at enterprise scale, Teradata is also introducing new AI Services leveraging its extensive history in delivering enterprise deployments and applying it to realise value from agentic projects.
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Gaps in an organisation’s existing strategies and implementations can be identified through a Customer Intelligence Maturity workshop, which then outlines the Teradata AI Services that can assist in solving challenges.
A new survey by NewtonX, conducted for Teradata, found that most organisations plan to boost customer experience investments, with 61% increasing spending on both general CX initiatives and AI-specific programs this year.
However, many organisations find that generic agents don’t deliver meaningful impact for enterprises with refined proprietary processes. The most effective agents are extensions of the enterprise data platform and the broader knowledge ecosystem.
Attempting to start with the agentic element fails because an accurate, integrated data foundation is both the hardest and most critical component when autonomous bots make customer-level decisions.
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This integrated approach, and the AI Services to make it happen, set Teradata’s Autonomous Customer Intelligence apart — translating decades of industry IP and contextual knowledge into AI models that enable agents to act in real time on raw data at enterprise scale.
“In the NewtonX survey, 77% of organisations were considering or evaluating the use of agentic AI to improve and automate CX functions,” said Sumeet Arora, Chief Product Officer at Teradata.
“That interest-level reflects a vision: Signals derived from customer data can be activated across marketing, service, risk, and product functions — transforming customer understanding into strategic business architecture that drives outcomes.”
“Success, however, hinges on industry-specific nuance, where Teradata’s unparalleled experience and AI Services can turn the most complex data challenges into competitive opportunities.”
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First Agentic Offering: Customer Lifetime Value (CLV)
Traditional AI models predict CLV, but Autonomous Customer Intelligence goes further by proactively increasing that value through real-time signals specific to customers — even across tens of millions of data points — enabling organisations to engage, retain, and grow their most valuable relationships.
Agent decisioning also improves with access to business context and signal-driven architecture.
Organisations prepared to trust this approach use AI-ready data products and scalable models to detect signals, personalise experiences, and guide decisions with speed, context, and precision. They need platforms that handle both data complexity and the simplicity agentic AI demands.
Teradata’s Customer Intelligence Framework and Teradata Services
Teradata addresses this with an end-to-end offering of products and services based on the business architecture called the Customer Intelligence Framework. It’s not about knowing the customer — it’s about designing the entire business to act intelligently and autonomously on that knowledge.
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Teradata’s AI Services help deploy the Customer Intelligence Framework at enterprise scale while maintaining security, governance, and cost predictability.
Teradata teams deliver data engineering and pipeline management; deploy capabilities to support AI, such as Enterprise Vector Store and ModelOps; and deliver integration and development for agents, including AgentBuilder and MCP server, all with a data governance structure designed to promote trusted and secure results.
The Customer Intelligence Maturity workshop can identify gaps in existing strategies and architecture that may impact autonomous customer intelligence and outline how Teradata can help.
Other key components of the framework include:
Data products form the foundational layer as reusable, AI-ready assets that organise customer behaviour, transactions, and interactions. Unlike reports or dashboards, they can be applied repeatedly to produce different insights without reconstruction.
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Built on integrated data, enabled by Teradata’s Industry Data Models (IDM) and Industry Analytic Schema (IAS), they support everything from Customer 360 to AI/ML deployment.
The analytics layer detects patterns, predicts outcomes, and delivers insights. Feature Engineering transforms raw data into meaningful signals for personalised engagement, while Enterprise Vector Store provides scalable vector management for generative and agentic AI use cases.
ClearScape Analytics is the in-database AI/ML engine for real-time intelligence, and AI Workbench offers an integrated workspace for secure AI deployment.
Signals represent the intelligence layer — unique, recognisable patterns within data that express context, behaviour, or intent to drive action. One sophisticated signal can generate value across multiple business functions, creating operating leverage from the noise.
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The framework detects and scores customer behaviour in real time, then embeds signals into workflows for automated decisions through Vantage Customer Experience (VCX).
Agents bring adaptability and automation — orchestrating decisions, interpreting intent, and activating intelligence in real time across three layers: AgentBuilder is for building and managing multi-agent systems; Teradata Agents offer pre-configured templates using curated data and repeatable data products; AI Applications operationalise customer insight at scale, enabling agentic workflows through natural language interfaces.
AI for CX Use Case Solutions are ready to deploy, packaged solutions to improve customer experience and continuously innovate on those solutions to leverage the latest advancements in AI. When deployed with the Customer Intelligence Framework, it maintains quick value and enables insight reuse across workflows.
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