AI agents, assistants and applications are only as good as the data they can reason, decide and are only as effective as the context they can access.. But most enterprise AI architectures still rely on fragmented data spread across multiple systems—limiting an agent’s ability to reason, explain decisions, and act with business context.
Join Mark Milinkovich, Director of Product Marketing and Daniel Morries, Solutions Engineer at Arango, for an inside look at the Arango Contextual Data Platform 4.0—and how organizations are building production-ready AI powered by a Contextual Data Layer..
In this 45-minute session, you’ll see how Arango unifies graph, vector, document, key-value, and search capabilities in a single platform—creating the trusted, real-time data foundation AI agents need to reason over enterprise context.
You’ll also see how the Arango Agentic AI Suite and its built-in AI services enable teams to:
- Automatically generate contextual knowledge models from enterprise data
- Optimize retrieval across graph and vector data
- Accelerate the path from AI prototype to production-ready agentic systems
Through guided product walkthroughs and real-world examples, we’ll highlight the innovations behind Arango 4.0 and the value they deliver to teams building and deploying AI applications, agents, and co-pilots.
What You’ll Learn:
- How to build a contextual data layer that connects enterprise data for AI agents and applications
- How AutoGraph™ transforms enterprise data into contextual knowledge models
- How AutoRAG™ optimizes retrieval across graph, vector, and document data
- How to simplify AI architecture while accelerating production deployment
If you’re building AI agents, co-pilots, or enterprise AI applications, this session will show you how to move faster—with a simpler, context-driven data architecture.
Speakers
Mark Milinkovich
Director of Product Marketing
Arango
Daniel Morris
Solutions Engineer
Arango