Unlock your productivity:
Own and track your data

Published 05 Oct 2025

You spend hours designing the ideal software architecture, only to discover your team is working from outdated diagrams, or worse, your latest changes got overwritten. In fast-moving projects, keeping everyone aligned can feel impossible. Now imagine tracking every change, experimenting safely and collaborating effortlessly, while staying fully in control of your models. With Git-powered version control for your C4 diagrams, you can achieve this productivity game-changer.

Effortless modeling

Summary

With Remodel, your data stays wherever you choose: on your computer, in Git or a cloud you trust. You’re always in control and we never see your work.

Everything is stored in an open text-based format, making it human-readable, future-proof and easy to move, back up or share.

Version-controlled C4 models let you experiment safely, track every change and collaborate without conflicts. Integrated with CI/CD, your diagrams are always aligned with code, creating a single source of truth. The history helps spot risks, track technical debt and onboard new team members with full context. Structured C4 models also guide AI to generate code that respects your architecture, keeping your system consistent, modular and maintainable.

You own your data

Your data lives exactly where you choose: on your own computer, in your company’s file system, in a Git repository or in the cloud service you already trust. You stay in control at all times. That way, your ideas are always yours. You’re not locked into ours servers or tied to a subscription just to keep access to your work.

We at Optimal Relations can never read or access your data. What you create is entirely private, visible only to you and those you choose to share it with.

Your data is saved in an open portable format. That means you can export it, share it or back it up whenever you want. Sharing with teammates is as simple as sending files or syncing with version control. Even if the tool disappears one day, your work remains fully accessable and when it’s time to archive, you can store your work in the same way you back up everything else, confident that it will remain accessible for years to come.

Read your data

At the core of owning your data is the choice of format. A text-based format flips that dynamic: your data becomes human-readable, tool-agnostic and future-proof.

You can open a file in any editor and immediately understand what’s inside.
Because text is inherently diff-friendly, you can track changes line by line. Tools like Git excel here, showing not just that something changed, but how it evolved over time.
Text-based data can be used across platforms and integrated with countless tools, from command-line utilities to cloud workflows. You’re never tied down.
A readable text-format remains accessible years into the future. Proprietary binaries, by contrast, can become unreadable as software ages out.

Choosing text as the foundation of your workflow isn’t just about storage, it’s about empowerment. It ensures you stay in control while making your work transparent, traceable and adaptable.

Version controlled file format

Being able to version control your C4 models has the same benefits as version controlling your source code and more.

Safety and reversibility

Rollback to stable versions: If a new edit to the C4 model breaks something or introduces confusion, you can quickly roll back to a stable version, keeping the diagrams clear and consistent.
Experimentation without fear: You can branch a C4 model to explore new ideas, test big structural changes or clean up issues. Knowing that if it doesn’t pan out, you can drop the branch without disrupting the stable model.

Collaboration and concurrency

Concurrent work: It lets multiple people work on the same C4 diagrams at the same time without overwriting each other’s changes. Everyone works on their own copy and then merge it all back together.
Conflict resolution: If two people change the same part of a C4 diagram, the system spots the conflict and gives you tools to work through it and merge the changes smoothly.
Single Source of Truth: It makes sure everyone’s working from the latest, correct version of the C4 model — no more confusion from passing around files like diagram-final-v2.drawio.

Traceability and accountability

Complete history: Every change to a C4 model is tracked with who made it, when, and a note on why. It gives full visibility so the team can quickly see the history.
Architectural review and quality: The clear history of changes makes it easy to review C4 model updates through pull or merge requests, helping the team catch issues and follow best practices before anything gets merged.

Automation and consistency

Automated rendering and publishing: The textual diagram files can be integrated into your Continuous Integration/Continuous Deployment (CI/CD) pipeline. On every commit to the main branch, the pipeline can automatically generate and publish the visual diagrams (PNG, SVG, etc) to a central documentation hub (like Confluence or a dedicated web portal). This ensures the published documentation is always up-to-date.
Always up-to-date: If the C4 diagrams are versioned alongside the code they describe then every commit, merge or branch could be validated to ensure that the codebase reflect the current state of the C4 model. This drastically reduces the likelihood of outdated or inaccurate documentation, which is a common problem when documentation is stored separately.
Single Source of Truth: Developers and stakeholders only need to look in one place for both the implementation and its architectural description, eliminating confusion over which diagram is the correct and latest version.
Enforced standards: Using version control allows you to enforce consistency. Every diagram must conform to some defined standard, ensuring all C4 diagrams across the organization have a standardized format.

Better discovery and searchability

Easy search: Since the C4 models are stored as plain text files, you can use the repository's search feature (e.g. GitHub search) to quickly find every diagram that references a specific component, container or technology. This aids in understanding the impact of a change across multiple systems.
Centralized Source of Truth: Keeping the diagrams in version control gives you one single source of truth for the system’s architecture, so you don’t end up with outdated or duplicate versions floating around.

Architectural risk and debt tracking

Tracking architectural volatility: Looking at the commit history lets you spot which parts of the architecture (Containers or Components) change the most. If something changes a lot, especially at the lower C4 levels, it could point to a fragile design, unclear ownership or a pile of technical debt.
Historical context for technical debt: When you decide to take on technical debt, like a shortcut to ship a feature, the version-controlled C4 model acts as the baseline for the “correct” design. Later, developers can check an earlier commit to see what the architecture was meant to be, making it easier to track and plan refactoring. Some teams even link an Architecture Decision Record (ADR) or Technical Debt Record (TDR) to the exact model version that introduced the debt.
Detecting architectural drift over time: You can compare the current model to the one from six months ago (or more) to visually and textually see the evolution. This makes it much easier to spot "architectural drift" where the actual system slowly diverges from the intended design due to numerous small and uncoordinated changes.

Enhanced onboarding and knowledge transfer

A "Time Machine" for new team members: A new developer can clone the repository and navigate the commit history to see the system's architecture at the time of a major feature launch or bug fix. This provides a contextual, chronological learning path that is far more effective than a static document. They learn how the system was built and not just what it is now.
The "Why" behind the "What" (when paired with code): When the C4 model is committed with the corresponding source code changes, the version control commit message often explains the reason for the change. This links the architectural modification to a business goal or technical rationale, providing crucial context that is often missing from standalone diagrams.

Enhanced context and accuracy for GenAI

Contextual RAG for AI: The C4 model can be integrated into a Retrieval-Augmented Generation (RAG) system. This gives the AI a clear and structured understanding of the system's Context, Containers and Components, allowing it to generate code that fits the architecture instead of just generating a syntactically correct snippet.
Architectural guardrails: GenAI often prioritizes speed, which can lead to code that introduces technical debt or violates established architectural patterns. The C4 model explicitly defines these patterns and boundaries. The AI can then use this as a set of "architectural guardrails" to enforce modularity, reusability and system-wide consistency, preventing the common problem of AI-generated code that is hard to maintain.
Accurate dependency mapping: The C4 model visually and structurally defines how components interact. This detailed dependency map enables the GenAI to correctly connect new code/modules, use the correct APIs and avoid creating tight coupling that would lead to problems later.

Unlock your productivity:Own and track your data