DocubotAI

Overview

• TwinCurrent built DocubotAI, an AI documentation platform, in beta at docubotai.app. It is our own SaaS product, not a client project, born from a problem we kept seeing in every codebase: documentation written once and never updated, or worse, docs that actively contradicted the current code.

• The platform connects to GitHub or Azure DevOps, analyses the codebase with AI, and keeps documentation synchronised through webhooks. When developers push changes, DocubotAI detects what changed and updates the relevant docs automatically. DocuAgent, a related tool, was merged into DocubotAI in January 2026.

The Challenge

• Documentation drifts from code within weeks of being written

• Developers spend time writing docs that are outdated before anyone reads them

• New team members onboard slowly because docs do not reflect the codebase

• Existing tools generate API references but miss architecture, patterns, and context

• No single tool handles the full lifecycle: analyse, generate, export, and keep current

System Architecture

• Repositories connect once; webhooks then drive everything. On each push, DocubotAI detects what changed and runs an AI analysis pass over the affected code to understand structure, dependencies, and patterns, not just signatures.

• Generated documentation is exported into the formats teams already use, so docs fit existing workflows rather than forcing a new tool. The webhook-driven loop is the core idea: it removes the manual step that causes documentation drift in the first place.

The Solution

• GitHub & Azure DevOps integration

  Connect repositories directly. DocubotAI reads your codebase, understands the structure, and keeps documentation synchronised with every push.

• Webhook auto-sync

  Set up webhooks so documentation updates automatically when code changes. No manual triggers, push code, get updated docs.

• Chat with your docs

  Ask questions about your codebase in natural language. Answers are grounded in your actual code and documentation, not generic responses.

• Multi-format export

  Export to Confluence, GitHub Wiki, PDF, or Markdown. Fits into your existing workflow without forcing tool changes.

• AI codebase analysis

  Understands code patterns, dependencies, and architecture. Generates docs that reflect how the code actually works.

• Always-up-to-date docs

  Continuous analysis ensures docs match the current state of the code, solving the drift problem at its root.

Integration Highlights

• GitHub & Azure DevOps

  Reads repositories and triggers on every push via webhooks.

• Webhook pipeline

  Push events drive automatic re-analysis and doc updates.

• Confluence & Wiki export

  Publishes docs into Confluence, GitHub Wiki, PDF, and Markdown.

Tech Stack

• Next.js

  Full-stack framework

• TypeScript

  Type-safe development

• Google Gemini

  AI analysis and generation

• PostgreSQL

  Primary database

Outcomes

• In beta at docubotai.app and under active development

• GitHub and Azure DevOps integrations cover the two most common Git hosts

• Webhook auto-sync eliminates the manual step that causes documentation drift

• Export to Confluence, GitHub Wiki, PDF, and Markdown fits existing team workflows

• DocuAgent merged into DocubotAI (Jan 2026), consolidating doc automation into one product

Interested in DocubotAI?

Try the platform or reach out to discuss how automated documentation can save your team hours every week.

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