Teradata launches AI Factory for on-premises AI development and data sovereignty

Teradata Brings AI Development to On-Premises Environments

Teradata has introduced AI Factory, a platform that lets enterprises build and deploy AI tools directly on their own systems. This move targets organizations concerned about cloud costs and data sovereignty, offering an alternative to cloud-only AI development options like Teradata's existing VantageCloud service.

Cloud AI development offers benefits such as managed infrastructure, scalable compute resources, and easy integration with third-party tools. But for AI workloads that demand large compute power, cloud costs can quickly escalate. Additionally, storing data across multiple geographic locations in cloud data centers raises compliance challenges for highly regulated sectors like healthcare and government.

On-premises AI development, while less flexible, can provide better cost control and regulatory compliance. Teradata’s AI Factory taps into this need by enabling secure, high-performance AI development within an enterprise’s own environment.

Leveraging Teradata’s Strength in Secure Analytics

Michael Ni, an analyst at Constellation Research, highlights Teradata’s traditional role in delivering high-performance analytics in secure environments. With growing interest in cloud repatriation, AI Factory aligns with the trend of bringing sensitive AI workloads back on-premises to avoid cloud cost volatility and regulatory scrutiny.

David Menninger from ISG Research points out that AI Factory addresses governance and data sovereignty concerns. Many leading AI platforms lack robust on-premises deployment options, making Teradata’s offering a notable alternative.

Based in San Diego, Teradata has a long history in data management and analytics. Following the surge in enterprise AI interest triggered by OpenAI’s ChatGPT, Teradata expanded its AI capabilities to meet customer demand.

AI Factory: What It Brings to the Table

According to Louis Landry, Teradata’s CTO, AI Factory combines trusted data management with AI development tools, giving enterprises the core components needed to build AI applications on a reliable data foundation. The platform is designed to help control costs and maintain data sovereignty.

Many organizations operate hybrid data environments. AI Factory supports this by allowing AI tools developed on-premises to run seamlessly across cloud, on-premises, or hybrid setups. The platform maintains a consistent environment regardless of deployment choice.

Key Features of AI Factory

• Integrated infrastructure with Teradata’s ClearScape Analytics, developer tools like JupyterHub and Airflow, plus support for model lifecycle management, compliance, and one-click deployment of large language models.
• Enterprise Vector Store that enables integration of structured and unstructured data with generative AI models.
• GPU connectivity through Teradata AI Microservices partnering with Nvidia for efficient algorithm execution.
• Data pipelines that support ingestion and integration of diverse data types and formats.

Michael Ni emphasizes that AI Factory gives analytics leaders the controls needed to scale AI projects without compromising compliance, cost certainty, or model integrity. While some competitors offer on-premises AI tools, AI Factory stands out as a unified, governance-grade AI stack that avoids cloud-related expenses.

Menninger notes that Cloudera offers a somewhat similar on-premises platform but relies on third-party tools for vector search and storage. Teradata’s solution is more integrated, though it faces challenges in brand recognition compared to hyperscalers and popular cloud-first platforms like Databricks and Snowflake.

Looking Forward

Teradata plans to focus on supporting agentic AI—systems that can perform tasks autonomously—aiming to enable a wider range of users to extract value from their data. This aligns with their longstanding goal of helping enterprises gain insights from complex data estates.

Expanding user reach will require more than technical upgrades. Menninger suggests Teradata could benefit from stronger marketing efforts to regain industry buzz, despite keeping pace with trends such as open table formats, open source tools, and multi-engine processing.

Ni recommends that Teradata prioritize AI governance and improve integration between its cloud and on-premises platforms. Enhancing these areas could drive better real-time intelligence, model integration, and consistent analytics across environments.

For IT and development professionals managing AI projects, Teradata’s AI Factory offers a compelling option for maintaining control over AI workloads, especially where compliance and cost are critical factors.