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Full-Stack Modeling Capabilities

From Raw Systems to AI-Ready Models

Reverse-engineer any source, model every layer, forward-engineer your target architecture, and give AI agents metadata they can query, all from one connected model.

A 45-minute call with a data modeling expert, not a sales pitch.

Database icons flowing through the Ellie logo into a data model diagram
Conceptual data model canvas for consumer auto insurance, showing Policy, Customer, Agent, Claim, Coverage and Vehicle entities linked by relationships
Large physical data model reverse-engineered from HubSpot, showing dozens of linked tables such as Deals, Contacts, Companies and their pipelines
Lumi AI assistant prompt for generating a dimensional logical model for deal analytics from HubSpot source tables

Four Capabilities, One Model

Everything Your Model Needs, Connected

Every capability below reads and writes the same model. Nothing is exported, re-typed, or explained twice moving from one to the next.

01

Reverse Engineer Models

Pull structure and meaning from 170+ existing systems before you draw a single entity.

See how it works
02

Semantic Modeling

Model conceptual, logical, and physical layers together, with one shared glossary underneath.

See how it works
03

Forward Engineer Targets

Generate DDL or YAML for the architecture you're building toward: dimensional, vault, mesh, lakehouse, or medallion.

See how it works
04

AI Context

Every model carries metadata your agents can query directly, through MCP, API, or YAML.

See how it works

Any Source, Understood

Start From What's Already There, Not a Blank Canvas

Database icons flowing through the Ellie logo into a data model diagram

170+ systems, one starting model

Connect to any of 170+ source systems and let AI generate synthetic table and column descriptions, so modeling starts from a real, documented structure instead of an empty canvas.

  • Ingests from 170+ systems and public APIs
  • AI-generated semantic names and descriptions
  • Sample-data or metadata-only, your choice

One Shared Canvas

Conceptual, Logical, and Physical, Together

Dimensional logical model canvas for deal analytics, showing a fact_deal table linked to dim_contact, dim_company, dim_owner, dim_pipeline, dim_deal_stage and dim_product dimension tables

One model, every layer, one glossary

Business and data teams build in one canvas instead of three disconnected tools. Entities, relationships, and definitions carry across every layer instead of drifting the moment they cross a handoff.

  • Real-time collaboration between business and data teams
  • One glossary connects every layer and every business domain
  • Logical and physical layers generate automatically from the layer above

Built for What's Next

Generate the Architecture You're Actually Building Toward

Large physical data model reverse-engineered from HubSpot, showing dozens of linked tables such as Deals, Contacts, Companies and their pipelines

Methodology-agnostic, push-ready output

Ellie doesn't force one target architecture. Model toward dimensional, data vault, mesh, lakehouse, or medallion, then generate DDL or YAML straight to Github, Gitlab, or Azure DevOps for dbt and the rest of the pipeline.

  • Supports dimensional, data vault, mesh, lakehouse, and medallion targets
  • Generates DDL or YAML directly from the model
  • Pushes straight to the existing pipeline, no manual re-typing

Context Agents Can Trust

Metadata Your Agents Can Actually Query

Lumi AI assistant prompt for generating a dimensional logical model for deal analytics from HubSpot source tables

Every model is AI-ready from the start

Every model carries AI-specific metadata the moment it's built. Through the Ellie MCP Server, assistants like Claude Desktop, Cursor, or Windsurf can query the model directly, not guess from a schema.

  • MCP server for direct model queries, not just chat
  • Works with OpenAI, Anthropic Claude, AWS Bedrock, Gemini, or Mistral
  • Text-to-model: draft a conceptual model from plain business requirements
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Across Every Capability

170+
systems reverse-engineered into models
10,000+
models in production today
60+
enterprise customers running them

What Practitioners Say

There are data governance and business analyst tools, and then there are data design and development tools. I don't see many connections between the two. Ellie seems to fill that gap.
Steve Hoberman
Steve Hoberman
Leading Data Modeling Expert
Ellie is an excellent option for modeling the data warehouse. It combines data documentation, modeling, and easy enterprise access, simple to use, yet flexible enough for a great modeling experience.
Bjarki Stefansson
Bjarki Stefansson
Senior BI Architect, Sidekick Health

One Model. Every Capability. All Connected.

Connects to 170+ systems and 10,000+ models already in production. A 45-minute call with a data modeling expert, not a sales pitch.