SaaS platform

The Agentic AI data platform for the enterprise

A governed semantic foundation that connects your enterprise systems to AI-driven applications. Not just a database. Not a generic knowledge graph. A multi-capability platform purpose-built for the era of Agentic AI.

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Why Data Graphs is different

Your schema is the AI's brain.
That changes everything.

In Data Graphs, the domain model is not just a constraint on your data. It is a complete, machine-readable description of what your data means: the entities, their properties, their relationships, and the business rules that govern them.

When an AI agent or human asks a question, the AI reads this schema and understands your domain the way an expert would. It writes precise GQL queries for structured data. It retrieves from the vector store for unstructured content. Every response is grounded in truth, cited from your data, and delivered through governed, permission-aware access controls.

No prompt engineering. No retrieval tuning. No data leaking to public models. Secure, private, hybrid RAG that works out of the box.

◎
Schema-driven intelligence
The AI has a total understanding of your domain. It reads your model, knows every entity, relationship, and rule, and writes precise, correct queries.
🔒
Secure, private AI
Your data never leaves your infrastructure. No data bleeds into public models. End-to-end encryption, enterprise SSO, and full audit trails.
⚡
Hybrid RAG, out of the box
Graph retrieval for structured questions, vector retrieval for unstructured content. Combined seamlessly. No configuration required.
🛡
Governed at every layer
Role-based access control, data stewardship workflows, and business rules enforced at the point of query. The same governance for humans and agents.

Vector finds similar. Graph finds true. Competing platforms offer retrieval. Data Graphs offers understanding. That is the difference between an AI that guesses and one that knows.

Platform capabilities
◎
Unified semantic model
Intuitive domain modeling tools to define your ontology. Business-friendly, no coding required.
⚡
Hybrid graph architecture
Best of ontology-based and property-label graphs. JSON-LD payloads, OpenCypher/GQL queries.
🤖
MCP-native Agentic AI
Built-in Model Context Protocol services. AI agents query your graph through a governed interface.
🔍
GraphRAG with hybrid retrieval
Combine graph traversal (GQL) and vector search. Cited, grounded responses from your data.
🛡
Data stewardship and governance
Workflow, roles, RBAC, audit trails, and compliance. Enterprise-grade data management out of the box.
🧩
Enterprise polystore
Full-text search, semantic search, vector DB, content graph, multimodal assets. One platform.
🎨
Best-in-class UI
Intuitive tools for data management, search, discovery, graph exploration, and AI chat. No code required.
🔗
API-first integration
Comprehensive REST APIs, webhooks, SDK, and MCP services for seamless integration with business systems.
How it works

From zero to AI-ready knowledge graph in days, not months

01

Model

Design your domain model with our no-code visual builder

02

Import

Upload data from CSV, API, or the UI with stewardship workflows

03

Integrate

Connect via API, webhooks, SDK, or MCP services

04

Deploy AI

Configure GraphRAG, connect agents, start querying

What you can build

One platform, many outcomes

Data Graphs is domain-agnostic by design. The same platform powers regulated labeling in agriculture, evidence-based medicine in healthcare, and content intelligence in media. Here are the most common patterns our customers deploy.

AI agents grounded in your data

Schema-driven hybrid RAG gives AI a total understanding of your domain. Precise queries, governed access, cited answers. No prompt engineering required.

See how it works →

Enterprise knowledge hub

Centralize organizational knowledge with natural language access. Everyone from executives to analysts can find what they need without writing code.

Data catalog and classification

Describe, classify, and govern datasets against multiple taxonomies simultaneously. A living, interconnected map of your data landscape.

Connected reference data

A single governed backbone for reference data, controlled vocabularies, and master records across all systems.

Content and media intelligence

Images, video, audio, and documents as first-class graph entities. Video key moments, content discovery, and AI-powered repurposing.

Archives and collections

Multi-modal knowledge graphs for archival content. AI-powered search, discovery, educational access, and research across any collection.

Competitive landscape

Not a database. Not a generic knowledge graph. A governed enterprise context layer.

Capability
Data Graphs
Traditional KGs
Vector DBs / RAG
Unified semantic model
✓ Full
Partial
No
True Hybrid RAG
✓ Built-in
No
No
Business rule enforcement
✓ In-graph
No
No
MCP-native AI interface
✓ Built-in
No
No
Agentic read + write
✓ Built-in
External
No, retrieval only

Ready to see Data Graphs in action?

Request a personalized demo and discover how the platform can transform your enterprise data.

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