Teradata launches AI-driven customer intelligence for real-time CX

Teradata has announced the launch of its Autonomous Customer Intelligence, a software and services package aimed at translating raw customer data into real-time, context-aware actions at scale.

The new offering adds a significant enhancement to Teradata's customer experience suite by embedding software agents across every stage of the data process, from product creation and signal detection to context interpretation and initiating autonomous responses within hybrid infrastructure environments. These agents rely on Teradata's intellectual property and industry expertise developed over 40 years addressing complex, mission-critical data challenges in various sectors.

Teradata believes that this software and services offering will allow customers to reduce the friction often encountered in applying advanced data expertise, supporting quicker returns on AI investments and delivering large-scale, enterprise-level customer intelligence automation.

To further support clients aiming to utilise Autonomous Customer Intelligence, Teradata is providing new AI Services built on its record of delivering enterprise-scale deployments. These services are designed to identify and address gaps in organisational strategies through the Customer Intelligence Maturity workshop, guiding customers on the most effective implementation to address their specific challenges.

A recent survey conducted by NewtonX for Teradata revealed that customer experience (CX) remains an investment priority. The findings indicated that 61% of organisations plan to increase spending on both overall CX initiatives and AI-focused programmes during the current year.

"In the NewtonX survey, 77% of organisations were considering or evaluating the use of agentic AI to improve and automate CX functions. 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," said Sumeet Arora, Chief Product Officer at Teradata. 

Teradata has emphasised that generic agents do not typically yield significant impact for enterprises with proprietary business processes. Effective AI agents, according to the company, are extensions of both the enterprise data platform and industry-specific knowledge bases. The company reports that the hardest and most important element is establishing an accurate, integrated data foundation, particularly when autonomous agents need to make decisions at the customer level.

The Autonomous Customer Intelligence offering distinguishes itself by applying Teradata's institutional expertise and contextual knowledge to AI models, enabling agents to act on raw data at scale for real-time outcomes.

Customer lifetime value

The first agent-driven capability launched is designed for Customer Lifetime Value (CLV) management. Unlike conventional AI models that merely predict CLV, this solution aims to increase customer value proactively using real-time data signals across large customer bases. This allows organisations to identify, retain, and grow their most valued customers more effectively. The company states that agent decision-making is improved further when integrated into data-driven architecture with full business context.

Teradata suggests that organisations adopting this approach should possess AI-ready data products and scalable analytical models for rapid, contextually aware decision-making. The platform is positioned as able to handle data complexity alongside the streamlined requirements of agent-driven AI applications.

Framework and services

Underpinning the offering is the Customer Intelligence Framework, a structured approach combining products and services to allow businesses to act on customer knowledge intelligently and autonomously. The framework includes a comprehensive suite of support, such as data engineering, pipeline management, vector database management, AI model operations, and agent integration - all within a data governance environment intended to provide security and predictable costs. The Customer Intelligence Maturity workshop remains a core service to identify areas for architectural improvement.

The framework operates through a series of interconnected layers:

• Data products: Designed as reusable, AI-ready resources organising behaviour, transactions, and interactions into assets suitable for various insights. Built on Teradata's data models and analytic schemas, these support projects ranging from customer profiling to AI and machine learning deployment.
• Analytics: The analytics layer is responsible for uncovering patterns, predicting outcomes, and transforming raw data into usable signals. This includes feature engineering, scalable vector management capabilities, and secure AI development workspaces.
• Signals: Acting as the intelligence core, signals are contextually rich patterns within the data, intended to drive business actions. The framework applies these in real time, integrating them into automated decision workflows.
• Agents: The automation layer consists of tools for building multi-agent systems, pre-configured agent templates, and applications that operationalise customer insights at scale via natural language interfaces.
• AI for CX Use Case Solutions: Packaged capabilities ready for immediate deployment and continuous AI-driven improvement, designed to accelerate value and ensure insight reuse across workflows.

According to Teradata, the Autonomous Customer Intelligence solution is already available, with further capabilities such as AgentBuilder entering private preview and additional agents scheduled for ongoing rollout to customers.