Build smarter AI with governed data
Activate every AI agent and use case with trusted, contextual, production-ready data at enterprise scale.
Why agent-ready data matters
of organizations don’t have or are unsure if they have the right data management practices for AI
Gartner, February 20251
of executives ranked lack of trust as a top challenge to realizing value from AI
PWC, July 20252
of senior business leaders said their organization’s AI adoption would be faster if they had stronger data infrastructure
EY, December 20243
Go from AI-ready to AI-activated
AI doesn’t fail because of the model. It fails because of bad data. That’s why so many AI initiatives stall before they deliver the intended value and why business stakeholders lose trust in AI-driven outcomes.
Truly activating AI requires a continuous pipeline of production-ready data that is:
- Accurate and observable. Quality issues are detected early and fixed fast.
- Contextualized. Every data point is enriched with business meaning and relationships.
- Governed by design. Policies, lineage, and access controls are embedded in workflows.
- Agent-ready. Data is delivered to AI assistants in a format they understand and can act on.
Key production-ready requirements
Ensure regulatory compliance across all systems. Apply governance rules automatically and confidently to enable fast AI development without introducing the risk of violations.
Wrap critical datasets into data products defined by contracts that specify usage, quality thresholds, SLAs, and access policies. Accelerate AI initiatives with reusable data.
Monitor enterprise data in real time so only validated data makes it into AI workflows. Leverage anomaly detection to catch issues early, avoiding bad recommendations and outputs.
Trace every piece of data that flows into an AI agent or model, and see how the data transforms over time. Make it easy to perform audits and explain how an AI-driven decision was made.
Use a knowledge graph and business glossary to give AI agents rich semantic context. Enable agents to understand relationships so responses align with how your business actually operates.
Close the last mile between AI-ready data and AI-powered experiences by connecting your knowledge graph-powered data catalog directly to AI tools such as Claude and ChatGPT.
Feed AI models and agents with meaning for more reliable and trusted outputs. A glossary and semantic layer enrich datasets with definitions, relationships, and business context.
Actian: Your partner for production-ready data
Actian Data Intelligence Platform provides AI systems and agents with high-quality data for reliable outputs, without adding risk or complexity. Powered by a federated knowledge graph, it offers automated data lineage and continuous quality monitoring.
This supports AI initiatives so you can scale with confidence and speed.
The platform delivers:
Knowledge graph-based data catalog
Benefit from a federated knowledge graph, business glossary, and semantic layer that allow AI agents to understand meaning, not just schema, for insights that reflect the state of your business.
Trusted data products
Take a contract-first approach to data products that define how AI agents can consume data safely. Use comprehensive contracts that specify usage parameters and quality guarantees.
Data lineage and governance
Ensure compliant AI with graph-based data lineage tracking and automated governance. See exactly what data feeds into your AI systems, its source, and how it changes over time.
AI-driven observability
Perform full data monitoring and anomaly detection across modern data stacks, without sampling or unpredictable cloud costs. Deliver agentic AI apps with confidence using reliable data.
Automated compliance enforcement
Keep AI projects audit-ready by embedding governance policies directly into data pipelines. Ensure every dataset feeding models meets regulatory and internal compliance standards.
MCP Server for agentic AI
Connect AI assistants and tools directly to governed, high-quality data. Enable AI assistants to query your data catalog, understand business terminology, and map data relationships.
Make AI work for you safely and at scale
Get DatasheetProduction‑ready data in action
What we value about the platform is its agility and the way its teams involve customers in managing the product roadmap, along with a very active user community for sharing best practices. On the technology side, it’s above all their compatibility with all clouds, especially AWS in our case, as well as the flexibility of their metamodel with the ability to create our properties that best suit our context.
1. Gartner, “Lack of AI-Ready Data Puts AI Projects at Risk,” February 2025.
2 PWC, “Midyear update: 2025 AI predictions,” July 2025.
3. EY, “EY research: Artificial intelligence investments set to remain strong in 2025, but senior leaders recognize emerging risks,” December 2024.