Exploring the Idea of an OpenMRS Company Brain – Looking for Community Feedback

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Hi everyone,

Over the past few weeks, I’ve been spending time exploring the OpenMRS ecosystem, reading through GitHub repositories, Jira issues, OpenMRS Talk discussions, the Wiki, documentation, pull requests, release notes, and community conversations.

One thing that stood out to me is how much valuable organizational knowledge exists across different systems.

For example:

  • Architectural decisions are often discussed on OpenMRS Talk.
  • Implementation details are buried in GitHub pull requests and review comments.
  • Bugs and feature discussions live in Jira.
  • Documentation is spread across the Wiki.
  • Historical context is distributed across years of discussions.

Each source is valuable individually, but together they form the institutional memory of the project.

As a newcomer, I found it difficult to answer questions such as:

  • Why was a particular architectural decision made?
  • Who currently maintains a specific subsystem?
  • What previous discussions led to a feature or design choice?
  • Which components would be affected by changing a particular module?
  • Has a similar issue already been discussed elsewhere?
  • What is the history behind a particular implementation?

Although search works well for finding documents, it doesn’t always reconstruct the relationships, decisions, historical context, or organizational reasoning behind them.

This made me wonder whether OpenMRS could benefit from something beyond traditional search or a chatbot over documentation.

The idea

I’ve been working on an experimental project that I currently call as OpenMRS Brain.

The idea is to continuously ingest knowledge from sources such as:

  • GitHub
  • Jira
  • OpenMRS Talk
  • OpenMRS Wiki

Rather than simply indexing documents, the goal is to compile organizational knowledge into a structured representation that understands things like:

  • ownership
  • dependencies
  • architectural decisions
  • historical evolution
  • relationships between components
  • release history
  • contributor expertise
  • provenance of information

The long-term goal is not to build another RAG chatbot.

Instead, the vision is to build a knowledge layer that future AI agents (or even developers) could use to understand how OpenMRS works.

Conceptually:

GitHub
Jira
Talk
Wiki

↓

Knowledge Compilation

↓

OpenMRS Brain

↓

Knowledge Graph
+
Temporal Organizational Memory
+
Reasoning Layer

↓

AI Agents
Developer Tools
Search
Documentation
Impact Analysis

Why I’m posting now

The project is still under active development.

Before taking it further, I’d really like to validate whether I’m solving a problem that OpenMRS maintainers and contributors actually experience.

I’d especially appreciate feedback on questions such as:

  • Does this seem like a problem worth solving?
  • Are there important knowledge sources I’ve overlooked?
  • What kinds of questions do contributors repeatedly struggle to answer?
  • What organizational knowledge do you wish were easier to discover?
  • If such a system existed, what capabilities would be most valuable?
  • Are there similar efforts within the OpenMRS community that I should be aware of?
  • What concerns would you have about a system like this?

I’m not looking for feedback on implementation details yet. At this stage, I’m primarily trying to understand whether the problem and the proposed direction are meaningful for the community.

Once the project reaches a more mature state, I’d be happy to share a demo and gather more detailed technical feedback.

Thank you for taking the time to read this, and I’d really appreciate any thoughts or suggestions from the community.

1 Like
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I greatly love the thoughtfulness that you have put in all this! Please keep it up. :smiley:

Just one small question, did you get a chance to look at our Slack integration with Unblocked?

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Thank you! I really appreciate the encouragement, and thanks for pointing me toward the Slack integration with Unblocked.

I hadn’t looked at it before, so I spent some time exploring it over the last couple of days. It was really helpful to understand what’s already available in this space.

The vision I described in my original post remains the same: not to build another RAG chatbot, but to explore a knowledge layer that continuously ingests information from GitHub, Jira, Talk, the Wiki, and other sources, compiles it into a coherent organizational representation, and keeps it up to date.

My hope is that this makes OpenMRS knowledge more legible for AI systems, so search, RAG, AI agents, automation, documentation generation, impact analysis, and other future tools can all build on the same organizational understanding instead of each reconstructing it independently.

I’d be very interested to hear your thoughts on whether you think a shared knowledge layer like this would be valuable for OpenMRS beyond what current tools already provide.

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