Why Medatarun
Most data stacks focus on storage, processing, and delivery. Governance focuses on rules, ownership, and processes. Documentation lives in tools that are rarely shared or enforced.
What is missing is a single place where data meaning itself is defined, explicitly, structurally, and in a way that both humans and machines can use.
This gap shows up differently depending on who you are:
- For CIOs, CTOs, and data leaders, it creates fragile systems and constant alignment work.
- For business teams, it leads to unclear definitions, conflicting indicators, low trust, communication is hard with IT.
- For AI initiatives, it results in systems that guess instead of reasoning.
The problem is not data, tools, or infrastructure. It is the absence of a shared, explicit and living reference for data meaning.
Static documentation has no operational value. That’s why it fails.
Medatarun makes data models operable.
If you want the full reasoning, you can read the complete problem statement.
What Medatarun is
Medatarun is an open source software that manages data models as explicit, shared artifacts instead of leaving them implicit in code, or spread across dashboards, Excel, Word files or wikis.
These models describe entities, relationships, attributes, rules, and operations that define the meaning of data.
Everything can be tagged and fully documented.
Medatarun exposes these models through:
- A user interface to explore, enrich and discuss them
- APIs and CLI tools for developers and tools
- Structured access (MCP) for AI agents
Medatarun does not store business data and does not replace your data stack.
It provides a concrete software layer where data meaning is defined, enriched, queried, and shared by humans and tools.
Medatarun is built with a plugin system. With plugins, you and your teams can add domain-specific commands, import or sync models from live systems, and connect and relate models to databases, alerting systems, and automated workflows.
When Medatarun becomes useful
It becomes relevant:
- when teams disagree on data definitions,
- when governance is done in scattered documents,
- when AI starts consuming data and “guessing” becomes a risk.
In these situations, making data meaning explicit becomes a prerequisite.
Working with Medatarun
Use it when structure and meaning become the bottleneck.
Medatarun is open source and early-stage. It is not a turnkey product, but a tool used during your analytics, development, governance and AI projects.
I’m an independent interim CTO/CIO (seij). In missions, Medatarun is one of the tools I use when a shared, explicit data model is the missing piece.
This work typically happens upstream: to align business and IT, reduce ambiguity, and de-risk data or AI initiatives.
If you want to discuss your context: https://www.seij.net
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