Workshop
AI Agent & Application Context Accelerator Workshop
Request a Complimentary Session for Your Team
Bring your Agentic AI use case.
We’ll design the AI Graph Data Architecture.
Build the graph-powered data and context foundation your AI needs today, with an architecture that can scale across every agent you build tomorrow.
Most organizations are building AI one use case at a time. Each new agent and application brings:
- new data sources
- new graph, vector, and hybrid retrieval methods
- new pipelines
- new context requirements
That works for the first few projects. But what happens when you’re running 10, 50, or 100 agents across the enterprise?
If your team is actively working through an AI use case, request your complimentary workshop. Bring your priority use case, and an Arango solution architect will work with your team to design the AI graph data architecture it needs to deliver accurate, explainable, and trusted results in production.
Bring your use case. We’ll help you map the architecture.
What You’ll Leave With
By the end of the workshop, you’ll have:
What We’ll Work Through Together
01
Start with your AI use case
What does your application or agent need to know, understand, and answer?
We’ll identify where missing relationships, incomplete context, or fragmented data may be limiting your results.
02
Map the data your AI needs
Identify the structured data, documents, vectors, relationships, and other enterprise data needed to create complete context.
03
Build the context
See how Arango AutoGraph can automatically discover relationships and generate the graph needed to give your AI richer business context, without months of manual graph modeling.
04
Design the right retrieval approach
Not every question should be answered the same way.
Explore when your application needs vector retrieval, GraphRAG, or a combination, and how AutoRAG can automatically adapt retrieval based on the question being asked.
05
Design for what comes next
We’ll look beyond your first application and identify how the same contextual data foundation could be reused across future AI applications and agents.
Why This Matters
Your first AI agent is a project. Your hundredth is an architecture problem.
Today, teams are building AI function by function and application by application.
Each project can easily create another set of pipelines, vector stores, graphs, retrieval logic, and data infrastructure.
As AI adoption grows, context becomes an enterprise-wide requirement.
Arango takes a platform-first approach.
Unify graph, vector, document, key-value, and search data in a single data platform. Automatically build and maintain the relationships that give your data meaning. Then dynamically retrieve the right context for each question and AI application.
Build once. Create context automatically. Reuse it everywhere.
Who Should Attend?
The AI Context Accelerator Workshop is designed for teams actively building or planning enterprise AI applications, including:
- Heads of AI & AI Platform
- Enterprise & Data Architects
- AI/ML Engineers
- Data & Platform Engineering Leaders
- CTOs & CAIOs
It’s especially valuable if you’re:
- Building AI agents or agentic applications
- Struggling to improve RAG accuracy or completeness
- Evaluating GraphRAG or knowledge graphs
- Connecting structured and unstructured data for AI
- Managing multiple AI applications with separate data architectures
- Thinking about how today’s AI projects will scale across the enterprise
Request Your Complimentary Workshop
Don't Just Build Your Next Agent. Build the Foundation for the Next 100.
Bring us an AI use case you're working on.
We'll help you determine what context it needs, where that context should come from, how it should be retrieved, and how the architecture can be reused as your AI strategy grows.
This is a collaborative working session, not a product presentation.