Ellie.ai
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About
Ellie.ai is a comprehensive cloud-based data modeling and governance platform designed to help organizations bridge the gap between business needs and technical data structures. It provides a collaborative environment where teams can create conceptual, logical, and physical data models. By focusing on the Data Product approach, it allows users to define the business meaning of data through a robust glossary before committing to technical implementation, ensuring that data architectures are built with a clear purpose and high quality. The platform features AI-assisted modeling capabilities that streamline the creation of entities and relationships. Users can leverage autodraw and entity grouping to visualize complex schemas quickly. Version 9 introduces an MCP (Model Context Protocol) Server, allowing developers to connect Ellie models to agentic workflows in tools like Cursor.ai, Windsurf, and n8n. This integration enables dynamic interactions where AI agents can interact directly with the established data models to assist in coding, automation, and documentation tasks. Targeted at data architects, engineers, and business analysts, Ellie.ai is particularly useful in enterprise settings where data governance is a priority. It integrates with major governance catalogs like Collibra and Microsoft Purview, as well as development tools like DBT and Azure DevOps (ADO). For large teams, the Enterprise edition offers hierarchical folders, role-based access control, and full version history with snapshots to maintain a single source of truth for the organization’s data assets. What sets Ellie.ai apart is its commitment to data culture and business alignment. Unlike traditional modeling tools that focus purely on technical DDL generation, Ellie emphasizes the business glossary and metadata management as core components of the modeling process. Its ability to export to various formats—including PDF for business stakeholders and DDL for database engineers—makes it a versatile communication tool that supports the entire data lifecycle from initial concept to physical implementation.
Pros & Cons
Supports the full modeling stack from business concept to physical DDL generation.
Features a built-in business glossary to ensure data definitions align across the company.
New MCP Server allows connection to AI development agents like Cursor and Windsurf.
Provides native integrations with enterprise catalogs like Collibra and Purview.
Includes robust governance features like version history, snapshots, and role management.
The Solo plan lacks collaboration features and advanced governance tools.
Enterprise pricing requires an annual commitment with a starting price of €1,000 per month.
API access and SSO are restricted to the Enterprise tier only.
Use Cases
Data Architects can design enterprise-wide conceptual models and sync them with logical and physical schemas to maintain architectural integrity.
Business Analysts can manage a centralized business glossary to ensure stakeholders agree on data definitions before technical development.
Data Engineers can automate the generation of DDL and track data lineage by integrating Ellie with DBT and ADO repositories.
AI Developers can utilize the Ellie MCP Server to feed structured data models into agentic workflows for automated coding and documentation.
Platform
Task
Features
• business glossary
• conceptual modeling
• mcp server integration
• data governance integration
• ddl export
• ai-assisted modeling
• physical modeling
• logical modeling
FAQs
What types of data models can I create in Ellie.ai?
Ellie.ai supports full-stack modeling, allowing users to build conceptual, logical, and physical models. You can also export these models as DDL for physical implementation or as images and PDFs for business documentation.
How does the AI-assisted modeling work?
Ellie uses AI to automate parts of the modeling process, such as generating entities and mapping source tracking. With the new MCP Server, you can also connect your models to agentic workflows in external AI tools.
Does Ellie.ai integrate with data governance tools?
Yes, the Enterprise plan offers integrations with popular data governance catalogs such as Collibra and Microsoft Purview. It also supports technical integrations with DBT and Azure DevOps repositories.
Can multiple people work on models together?
The Enterprise plan includes collaboration tools and role management, supporting modeler, contributor, and read-only profiles. This allows teams to manage hierarchical folders with specific security settings.
Pricing Plans
Solo
EUR49.00 / per month• Single User License
• Full stack modeling (conceptual, logical, physical)
• AI assisted modeling
• Business Glossary
• Export to PDF, Image, or DDL
• Entity grouping and autodraw
• Notes and annotations
Enterprise
EUR1000.00 / per month (billed annually)• Collaboration tools for teams
• Hierarchical folders with security
• Advanced AI capabilities
• Collibra and Purview integrations
• DBT and ADO repository support
• User profiles (modeler, contributor, read-only)
• Full version history and snapshots
• SSO and API access
• Dedicated Customer Success Manager
Job Opportunities
AI-Native Full-stack Senior Developer
Design complex data architectures with AI-powered conceptual, logical, and physical modeling to align business requirements with technical execution for data teams.
Benefits:
Extensive health insurance
Wellness support
ePassi for lunch, sports, and culture
Gym access
Options program
Experience Requirements:
Strong proficiency in TypeScript, Node.js, PostgreSQL, and React
Experience building with Agentic Workflows, Orchestration, or RAG
Understanding of Context Management and LLM data integration
Professional fluency in English
Experience in fast-paced startup environments
Other Requirements:
AI-Native Mindset
Understanding of LLM trade-offs (latency, cost, reliability)
Team player (low ego, high impact)
Familiarity with Data Modeling or Data Governance
Hands-on with AWS and Docker
Responsibilities:
Agent Orchestration for complex data modeling tasks
Developing context-aware UI components
Design and implementation of A2A Architecture
Translating requirements into solid technical blueprints
Acting as a critical quality gatekeeper for code
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