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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
Web
Task
data modeling

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

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Ellie.ai

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.

engineeringhybridHelsinki, FIfull-time

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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