At-a-Glance
Unlock AI Value from Your Existing ArangoDB Deployment
Expanding your ArangoDB deployment with the Agentic AI Suite enables teams to operationalize enterprise data for AI—supporting both human-driven investigation workflows and contextual retrieval for agents and co-pilots.
Key Value Drivers
Arango’s Agentic AI Suite extends ArangoDB with services for building context-grounded AI agents and co-pilots, including GraphRAG for knowledge-graph grounding, AQLizer for natural-language querying, and graph-based ML/analytics to improve signal, reasoning, and retrieval.
As organizations deploy AI agents and co-pilots for customers, partners, and employees, success depends on trusted answers grounded in enterprise data and controlled access to live systems. The value drivers below show how expanding from ArangoDB to the Agentic AI Suite enables dependable outcomes without replacing the database foundation.
| Capability | Outcome |
|---|---|
| Interactive Relationship Exploration | Use Graph Visualizer to explore and analyze relationships across enterprise data — supporting investigation, troubleshooting, and dependency analysis workflows. |
| Natural Language Data Interaction | Enable users and agents to query operational data using natural language via AQLizer — accelerating investigation and knowledge discovery. |
| Vector-Enabled Retrieval | Store and retrieve vector embeddings alongside graph and document data to support semantic search and AI retrieval workflows. |
| Contextual AI Grounding | Combine vector similarity with graph relationships to ground AI responses in enterprise context. |
| Unified Multi-Model Storage | Manage vector, graph, and document data within a single system — reducing integration complexity for AI applications and agents. |
| Operational Pattern Detection | Apply graph analytics to identify dependencies, anomalies, and operational signals across connected enterprise data. |
Outcomes and Benefits
| Outcome | Benefits |
|---|---|
| Faster Time-to-Production | Move from “database + documents” to working copilots faster using packaged GraphRAG workflows and UI-driven setup. |
| Higher answer quality + fewer hallucinations | Ground responses in a knowledge graph + retrieval context from your enterprise data instead of relying on model memory alone. |
| More self-serve data access | Enable business and engineering users to ask questions in natural language and generate AQL for validation and reuse. |
| Better detection and prioritization | Improve ranking, pattern discovery, and prediction using graph algorithms and graph ML on connected data. |
| Lower integration riskat Scale | Expand your current ArangoDB footprint rather than building a new “AI data stack” from scratch. |
How It Fits in the Platform
For organizations already running ArangoDB, the Agentic AI Suite extends connected data management into production-ready AI applications. ArangoDB remains the system of record for operational and relationship-rich enterprise data, while the Agentic AI Suite enables teams to build AI agents and copilots that retrieve and reason over this data using GraphRAG and vector search.
As AI initiatives move to production, the Arango Platform Suite provides the operational foundation for deployment and management at scale, including standardized deployment, lifecycle management, and RBAC across cloud, on-premises, and hybrid environments.
Together, these capabilities allow teams to operationalize contextual AI without replacing their existing database.
Why Choose Arango?
The roadmap to the Arango Contextual Data Platform is designed for organizations that want to operationalize AI on their existing enterprise data without replacing the database foundation they already trust.
Build on What You Have
Use your existing ArangoDB deployment to build AI apps, agents, and copilots with contextual retrieval and natural-language workflows.
Expand at Your Pace
Introduce Agentic AI capabilities incrementally—enabling GraphRAG, vector-enabled retrieval, and AI-assisted investigation as business needs evolve.
Operationalize AI in Production
Extend deployments with lifecycle management and RBAC for governed, scalable operations across cloud, on-prem, and hybrid environments.
Avoid Platform Rebuilds
Transition from data management to contextual AI without standing up a separate AI data stack or replatforming existing applications.
Ready to accelerate your intelligent application journey?
Contact us today to schedule a demo and learn how the
Arango Contextual Data Platform can transform your business..