Agentic AI plans, decides, and takes action autonomously. But to function safely and accurately, autonomous AI agents need more than data: they need a deep understanding of your business. A Stardog Enterprise Knowledge Graph (EKG) provides that understanding. (View Highlight)
Agentic AI is goal-oriented, unlike Generative AI. Agents, like those in self-driving cars, plan and execute complex tasks across different applications and systems—all without human intervention. (View Highlight)
To do all that, Agents need to chain together people, products, processes, customers, and outside information like “Cargo Ship A is owned by Company B” or “Federal Regulation X applies to Product Y” and they have to do it all in real time. (View Highlight)
Large Language Models (LLMs) can generate and process language, but because they are trained on massive, public datasets, they don’t understand the web of relationships between your specific business data. They lack the specific, grounded context of your enterprise data ecosystem. Relying on LLMs alone introduces serious risk of hallucinations, omitted data, or downright harmful actions. (View Highlight)
Knowledge graphs are the appropriate target for exploiting LLMs for business value, since they are machine-readable data structures representing semantic knowledge of the physical and digital worlds. (View Highlight)
Stardog’s EKG maps the relationships between every piece of enterprise data, wherever it resides. The EKG is a single, always-current source of truth. AI Agents can leverage this enterprise-wide view to reveal new insights that require a complete picture of the data. (View Highlight)
A Stardog EKG connects, contextualizes, and governs enterprise data. That data can then be integrated with LLMs to provide the basis for AI Agents. It is the only way to ensure safe, reliable AI automation and insights. (View Highlight)
Trustworthy AI in the most demanding industries requires accurate, grounded, and explainable actions. Stardog makes this possible by providing a trusted, contextualized knowledge graph that acts as a single source of truth for your AI agents. This shared context is especially vital for agentic systems, giving them a common language to access all of your organization’s data. As a result, your LLM-powered agents can make better, more reliable decisions, uniting the versatility of LLMs with trusted, structured enterprise data. (View Highlight)
The semantic layer defines meaning and relationship. AI Agents can then reason based on those relationships and understand enterprise-specific ideas like teams, policies, and systems. Enterprise teams can move beyond basic data connectivity to actionable understanding. (View Highlight)
Stardog’s EKG is a virtualized representation of your data. Data is not moved or copied. The Knowledge Graph allows Agentic AI to scale across the enterprise, providing unified, real-time access across cloud, on-prem, or legacy systems through our API and Model Context Protocol (MCP) capabilities, all while leaving data in its original location. (View Highlight)
Gain confidence and control. Unify fragmented data, modernize analytics infrastructure, and accelerate digital transformation. Invest in a scalable, future-ready platform for trusted AI. (View Highlight)
