Teradata Services are a comprehensive suite of offerings designed to help organizations unlock the full value of their data whether they operate in the cloud, on-prem, or a hybrid architecture. They include solutions for modernization, optimization, and AI-driven transformation, enabling businesses to accelerate analytics, improve operational efficiency, and scale innovation across the enterprise.

The primary audience includes business and IT leaders, data and analytics teams, and organizations seeking to modernize their data platforms, optimize performance, and leverage AI for competitive advantage. These services are ideal for enterprises that want to reduce technical debt, improve customer experiences, and achieve measurable business outcomes.

Companies choose Teradata Services because of Teradata’s decades of proven expertise, continuous innovation, and customer-centric approach. Teradata integrates AI into its offerings, enabling organizations to move beyond pilots and scale AI across the enterprise with trusted data and industry-specific workflows.

Teradata Services help organizations overcome challenges such as:

• Accelerating time-to-market for analytics and AI solutions.
• Reducing operational costs and technical debt.
• Improving system performance and reliability.
• Ensuring data security, compliance, and governance.
• Scaling AI and analytics across complex ecosystems.

Teradata Services enable organizations to scale AI beyond pilots by providing trusted data, embedded expertise, and industry-specific workflows. They offer production-grade AI use cases, packaged accelerators for rapid deployment, and governance frameworks to ensure secure and compliant AI adoption.

Teradata experts are deployed to help organizations achieve value through the rationalization and deployment of AI within the enterprise. These experts are operationalizing AI agents at enterprise scale with a foundation of trusted data and contextualized business knowledge leveraging the latest in technology delivering value without sacrificing performance and cost.

AI Services will include a variety of existing and soon to be developed services. Each service will deliver:

• AI Activation: The foundational activities required to enable a connected analytic ecosystem. These can include activation services like MCP Server deployment, Enterprise Vector Store, and AgentBuilder configuration as well as modernization services such as data pipeline modernization or semantic modeling to support the development of reusable data products. The services required for this layer will be customizable based on the customer’s current level of maturity.
• AI Value Realization: Agile deployed sprints to deliver AI outcomes in production. These may involve the use of application products like VCX or CIM in addition to the outcome-based service. Plus, access to AI for CX use case solutions give users a head start to deliver great customer experiences through packaged solutions for rapid, low-cost deployment.
• AI Sustainment: The model operations and sustainment required to ensure AI use cases deployed to production remain relevant and leverage the latest advancements. 

AI Services provides sprint-based delivery, expert-led governance, and reusable data products that help organizations prioritize high-impact use cases and bring AI models into full production with ongoing support. POCs often focus on experimentation whereas productionization at enterprise scale requires a knowledge platform with trusted data, security, and governance to not sacrifice performance and cost.

Research shows 95% of AI pilots fail due to poor prioritization, governance, and execution, not due to technology limitations. Teradata solves this with embedded experts, a unified knowledge platform, a proven methodology based on our own experience in deploying AI use cases, and agile delivery to turn pilots into scalable, sustainable AI deployments.

AI Services supports a wide range of industries (including financial services, healthcare, retail, and telecom) with use cases. For instance, these use cases include anti-money laundering, customer personalization, image processing, anomaly detection, churn prediction, and more.

AI Services can be utilized in a variety of use cases across industries. Some use cases include:

• Healthcare Image Processing: Secure, scalable processing of mammogram data using parallel workflows and in-database model deployment.
• Agentic Hyper-personalization in Healthcare: Patient-specific AI agents monitor, predict, and engage in real time across the care ecosystem.
• Customer Engagement with VCX: VCX drives real-time, personalized messaging that boosts engagement and revenue while reducing costs.
• AI for CX in Banking: In-database language models enable secure, scalable customer experience transformation.
• Anti-Money Laundering in Retail Banking: Replaced legacy AML systems with scalable AI for faster training, deployment, and compliance.
• Anomaly Detection: In-database modeling reduces false positives and accelerates regulatory reporting.

Yes. As part of the AI activation layer, Teradata offers modernization services such as data pipeline optimization and data modeling to support reusable data products and prepare your ecosystem for agentic AI.

Teradata uniquely combines embedded expert consulting with enterprise-grade AI technology to solve two critical challenges: getting agentic use cases into production and prioritizing those that deliver real business value.

Yes, the services are designed to meet customers wherever they are on their AI journey—whether at foundation, growth, expansion, or mastery—with tailored assessments, workshops, and delivery models.

The offering includes innovations like Enterprise Vector Store, MCP Server, AgentBuilder, and AI Workbench, and more coming soon.

AI Services supports cloud, on-premises, and hybrid environments, and is available globally with flexible delivery options.

Built-in AI governance ensures auditability and policy enforcement, with embedded experts guiding implementation and sustainment to meet enterprise standards.

AI Sustainment services ensure that deployed use cases remain relevant and optimized, leveraging the latest advancements in technology and model operations.