At-a-Glance
Arango AutoGraph Studio
Arango AutoGraph Studio is the web interface in the Agentic AI Suite that turns enterprise documents into an AI-ready Context Graph, then optionally deploys retrieval-augmented generation (RAG) retrievers on top of it. One guided workflow covers upload, model configuration, graph building, retriever deployment and querying, so AI teams move from raw content to grounded answers without stitching tools together.
How it Works
01
Upload
Add documents and sort them into categories.
02
Configure
Pick chat and embedding models, plus optional image analysis.
03
Build
Choose depth, from Vector only to Graph + images.
04
Deploy
Launch retrievers on the Context Graph.
05
Ask
Query in Instant or Deep Search mode.
Outcomes and Benefits
What AI teams get from one guided workflow.
| Outcome | What it means for your team | Powered by |
|---|---|---|
| One workflow, not a toolchain | Upload, build, deploy and query in one interface, with no separate graph, vector and retrieval tools to integrate. | AutoGraph Studio |
| Graph results, no graph specialists | AutoGraph extracts entities and relationships and picks a strategy for each cluster, so there are no ontologies to hand-build. | AutoGraph + RAG Strategizer |
| Cost and depth matched to the job | Choose Vector only for speed and cost, or Graph + images for depth, project by project. | Build complexity settings |
| Grounded, traceable answers | Answers draw on entities, relationships and source documents, supporting explainability and audit. | Context Graph |
| The right mode for every question | Instant for fast, single-pass answers. Deep Search for complex, multi-hop questions. | AutoRAG + Deep Search |
| Start with the graph, grow into retrieval | Stop at the Context Graph or add retrievers later, then automate with the Importer and AutoRAG application programming interfaces (APIs). | Two-stage workflow |
Know Your Graphs
Corpus Graph
Documents, chunks and clusters extracted from your content.
+
Knowledge Graph
Entities and relationships (GraphRAG) or embeddings (VectorRAG), built for each cluster.
=
Context Graph
The complete, AI-ready foundation your agents reason over.
Why AutoGraph Studio
Faster to first answer
A guided path from raw documents to a queryable graph.
Simpler to run
One interface replaces separate AutoGraph and GraphRAG tools.
Built to grow
Start graph-only, add retrievers, then automate
through the APIs.
Ready to see your documents as a context graph?
See AutoGraph Studio turn your content into grounded answers.