AI Tool Series – Episode 60: Keep Your API Documentation Always in Sync with DeepDocs AI

Maintaining accurate API documentation is a constant challenge for engineering teams. As code evolves, documentation often lags behind, leading to confusion, integration issues, and wasted developer time. DeepDocs AI addresses this problem by automatically keeping API documentation aligned with your source code—without requiring manual updates.

This article explains what DeepDocs AI is, how it works, and why it can be a valuable addition to modern development workflows.

What Is DeepDocs AI?

DeepDocs AI is an automated documentation tool that keeps your API documentation up to date by continuously tracking changes in your codebase. Instead of manually editing documentation every time an API changes, DeepDocs AI monitors your Git commits, detects relevant modifications, and updates the documentation accordingly.

In simple terms:

• When a new API is added, DeepDocs AI identifies it and adds it to the documentation.
• When an existing API is modified, the documentation is updated to reflect those changes.
• When an API is removed from the code, it is also removed from the documentation.

This ensures that your documentation always reflects the current state of your APIs.

How DeepDocs AI Works

DeepDocs AI integrates directly with your Git repository and operates as part of your normal development process.

1. Git Integration

To get started, you install DeepDocs AI in your Git account and grant access to the repository you want to monitor. You can choose specific repositories where API documentation needs to stay in sync with the source code.

2. Source and Target Configuration

DeepDocs AI requires two key inputs:

• Source code directory – where your backend or API code resides.
• Documentation directory – where your API documentation files are stored (for example, REST client docs or Swagger files).

By mapping the source code to the documentation folder, DeepDocs AI understands where to read changes from and where to apply updates.

3. Continuous Scanning

Every time a commit is made:

• DeepDocs AI scans the commit.
• It identifies changes in API definitions, request/response fields, validations, or endpoints.
• A scan report is generated showing what was detected and what documentation was affected.

Each scan includes metadata such as:

• Scan time
• Triggering commit
• Outdated documents updated by the scan
• Credits consumed for that scan

Automatic Documentation Updates via Pull Requests

When DeepDocs AI detects a change, it does not directly modify your main branch. Instead, it:

• Creates a separate branch
• Generates a pull request (PR) with the documentation updates
• Clearly highlights what was added, modified, or removed

This allows teams to:

• Review the changes
• Verify accuracy
• Merge the updates confidently

For example:

• If a field, such as mobileNumber, is removed from an API and a new field, like age, is added, the documentation is updated to match.
• If an entire API endpoint is deleted from the codebase, DeepDocs AI detects this and removes the corresponding documentation entry.

This review-first approach keeps teams in control while eliminating manual effort.

Preventing Documentation Drift

One of the biggest advantages of DeepDocs AI is its ability to prevent documentation drift.

Documentation drift happens when:

• A developer updates an API
• The changes are merged into the codebase
• The documentation is forgotten or partially updated

Over time, this leads to outdated or misleading documentation. DeepDocs AI solves this by automatically syncing documentation with every relevant commit, ensuring that documentation always reflects the latest implementation.

Supported Documentation Formats

DeepDocs AI is flexible and works with multiple API documentation formats, including:

• Swagger / OpenAPI
• REST client documentation
• Other structured API documentation formats

This makes it suitable for a wide range of projects and tech stacks.

Why Use DeepDocs AI?

DeepDocs AI provides several practical benefits:

• Eliminates manual documentation updates
• Keeps API documentation continuously in sync with code
• Reduces errors caused by outdated documentation
• Saves developer time and effort
• Fits naturally into Git-based workflows

By automating documentation updates and integrating seamlessly with version control, DeepDocs AI allows teams to focus more on building features and less on maintaining documentation.

Conclusion

Accurate API documentation is essential, but maintaining it manually does not scale. DeepDocs AI offers a reliable, automated approach by monitoring Git commits and keeping documentation aligned with real code changes. With pull request–based updates, support for common documentation formats, and simple pricing, it provides a practical solution to one of the most common challenges in software development.