What does it mean to have trusted data? Trusted data means seamlessly integrating and harmonizing data across an organization. It’s a foundation of reliability, accuracy, and governance that’s essential for every enterprise.
Without securing and harmonizing your data in an open ecosystem, investments in AI won’t pay off. That's why enterprises are adopting trusted data and Trusted AI strategies with the help of Teradata—the Trusted AI company.
Teradata is the Trusted AI company
For more than four decades, Teradata has forged a track record of building a company’s "golden record"—the foundation of trusted data that’s required for mission-critical workloads. We’ve built our platform to be the best in class at scale, so we know what it takes to grow fast and stay cost-effective.
As AI ambitions grow, Teradata continues to guide companies through their AI journeys by offering:
- Best-in-class in-database AI/ML functions and open API integrations
- The ability to bring your favorite models in the most open and connected ecosystem
- The freedom to innovate with Teradata AI Unlimited
- Better decision-making for both business and technical teams with ask.ai
- Improved productivity and faster ROI with ClearScape Analytics™
Trust accelerates opportunity
Trusted AI can be incorporated across your organization’s analytics and AI/ML solutions. From predictive AI/ML to generative AI initiatives, Trusted AI is both relevant and necessary for success.
Deliver better forecasts with predictive AI/ML
Trusted AI is crucial for the in-database functions and data pipelines used in your predictive AI/ML projects.
You can quickly elevate your decision-making with Teradata VantageCloud, the only platform to offer a massively parallel processing (MPP) architecture that enables best-in-class vertical and horizontal scaling of models.
Create confidently with generative AI
Make your data lineage for generative AI use cases more explainable, accountable, and valuable with Trusted AI.
VantageCloud helps you better understand both your small language models (SLMs) and large language models (LLMs) by integrating the output with features and data sources. This includes the ability to store and integrate prompts, embeddings, and retrieval augmented generation (RAG) queries.
Maximize the AI opportunity today
Drive value from trusted and cost-effective AI innovation across the enterprise with the most complete cloud analytics and data platform for AI.
Trusted AI principles
Accountability in all parts of the AI lifecycle
When you take a human-centered approach to AI, you improve compliance with safety and privacy concerns, reinforce ethical and responsible standards, and limit potentially harmful impacts on our environment and society.
Focusing on people in Trusted AI includes:
- Providing reliable and effective data security
- Introducing energy-efficient practices
- Protecting personally identifiable information (PII)
- Preventing bias issues with models and data training
Flexibility and faster innovation with open AI ecosystems
Transparency is being able to understand how and why an AI-driven decision was made, and why it’s both fair and equitable—even if it isn’t the modeler’s own choice.
You can drive transparency by:
- Offering visibility into how models use data and comply with regulations
- Validating data sources as trustworthy before AI implementation
- Making model outputs explainable—and accountable—to human decision-makers
Cost-effective growth by scaling AI breakthroughs
Better reliability, speed, and accuracy will make the ROI of your AI models far outweigh the cost of experimentation.
Value creation starts with identifying use cases. Your breakthrough AI solutions can range from big ideas to incremental improvements:
- Building your own custom LLMs or integrating with partners
- Updating recommendation engines to be powered by generative AI
- Using natural language interfaces for insights, code generation, and metadata analysis
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