The 8 Best AI Documentation Tools for Legacy Code

Quick summary

This guide reviews the best AI documentation tools built to handle outdated, complex systems. If you need faster onboarding, compliance-ready records, or deeper system insights, these tools help document legacy code without starting from scratch. Visit the Kodesage blog for more insights on legacy modernization and documentation. 

Struggling to document legacy code? AI can help

Legacy codebases are difficult to document. The original developers are often long gone, documentation is missing or outdated, and the logic is tangled deep within years of patches and quick fixes. 

Yet teams still need to maintain, audit, and modernize these systems. Manual documentation is slow, inconsistent, and rarely keeps up. 

That’s where AI tools come in. Designed to analyze code, trace functionality, and generate documentation automatically, they help teams save time, reduce errors, and gain clarity fast.

In this Kodesage guide, we’ll highlight the best AI documentation tools built specifically for legacy code.

What are AI documentation tools?

AI documentation tools are software solutions that use artificial intelligence to generate or assist with technical documentation. They analyze source code, system behavior, and related assets to create human-readable explanations.

These tools are especially useful for large or complex codebases, including legacy systems, where manual documentation is slow or incomplete.

Most work by applying language models or pattern recognition to identify code structure and logic, making them a modern alternative to traditional documentation methods.

Why AI documentation tools matter

• Save developer time: Automate the documentation process so engineers can focus on building, not writing.
• Reduce knowledge gaps: Fill in missing context for legacy code when original authors are no longer available.
• Improve onboarding speed: Help new developers understand complex systems faster with clear, AI-generated explanations.
• Support safer changes: Accurate, up-to-date docs reduce the risk of breaking things during refactoring or updates.
• Aid compliance efforts: Create audit-ready documentation for regulated industries without relying on manual effort.

A summary of the best AI documentation tools for legacy code

8 top AI documentation tools to consider for legacy code

1. Kodesage

Kodesage is an AI-powered legacy knowledge platform built specifically for complex, aging systems built on legacy programming language. It’s designed to help teams understand, modernize, maintain, and document legacy code in secure on-premise environments.

By integrating source code, issue ticketing systems, database schemas, and offline docs, Kodesage builds a living knowledge base for your systems. Users can query it in natural language, map system dependencies, and generate real-time, audit-ready documentation that stays synced as the code evolves.

Key features

• Living knowledge base: Connects to multiple data sources natively, and remains up to date as the codebase evolves, ensuring always current documents
• Legacy programming specific intelligence: Performs intelligent code chunking and relationship mapping, and has contextual understating of legacy code structures
• Choose preferred LLMs: The knowledge base, built on legacy specific code intelligence ensures that Kodesage can work with any LLM model
• Pre-built document library: Provides a library of customizable software document templates covering various use cases (e.g. user guides, API documentation, regression test catalogs, logical system design documentation and more)
• Visual system dependency maps: Creates visual diagrams of systems and dependencies in documents
• On-premise & air-gapped deployment: Although also offering VPC cloud deployments too, Kodesage has primarily been built for secure on-prem environments to ensure maximum data privacy

Pricing

Kodesage pricing is based on the number of systems, and not based on feature usage. One full system is a project, and within projects there are no limits on feature usage.

Pros

• Connects to docs, databases, and trackers to make complex code easier to understand and maintain.
• Creates and updates documentation automatically as code changes.
• Supports on-prem, VPC, and air-gapped deployments for security needs.
• Allows you to use your own LLM models for privacy and compliance.
• Helps new developers get up to speed faster with current documentation.
• Keeps documentation ready for audits and compliance checks.

Cons

• Designed primarily for enterprise teams, not individual developers

2. Docusaurus

Docusaurus is a popular open-source documentation framework maintained by Meta (Facebook), designed for building fast, versioned, and content-rich documentation websites. It’s widely used for developer portals, open-source projects, and product documentation because it combines markdown simplicity with a modern React-based frontend.

Unlike AI-driven tools, Docusaurus focuses on giving teams full control over content, layout, and deployment, making it ideal for organizations that prefer a customizable, self-hosted solution over SaaS tools.

Key features

• Markdown-based authoring: Write documentation using Markdown or MDX (Markdown with React components), combining simplicity with dynamic interactivity.
• Versioning and localization: Easily maintain multiple documentation versions and languages — perfect for long-lived or global projects.
• Customizable React theme: Extend or override the default UI with React components, giving you full branding control.
• Built-in search and navigation: Includes powerful sidebar configuration, Algolia DocSearch integration, and automatic table of contents generation.
• Static site generation: Produces optimized, SEO-friendly static pages that can be hosted anywhere — from GitHub Pages to enterprise servers.

Pricing

Docusaurus is completely free and open source under the MIT license. However, teams must handle hosting, maintenance, and custom setup themselves.

Pros

• Fully customizable and open source — no vendor lock-in
• Markdown and MDX make authoring flexible yet simple
• Strong community support and ecosystem of plugins
• Ideal for long-term, versioned documentation of legacy or evolving systems

Cons

• Requires setup, maintenance, and developer involvement
• No built-in AI or code sync features — integration must be done manually
• Collaboration features depend on external tooling (e.g., GitHub, CMS integrations)

3. Mintlify

Mintlify is an AI-driven documentation platform that generates clean, developer-friendly documentation directly from your codebase. 

This tool lets you link your Git repository so it can automatically scan your code, detect structures, and produce well-structured documentation. It’s especially helpful for teams that need consistently formatted, easy-to-navigate docs without writing them manually.

Key features

• Git sync and version control support: Automatically updates documentation whenever code changes occur, keeping docs aligned with your repo.
• Visual editor with web-based UI: Allows team members to write and update documentation without needing to work in Git.
• AI chat assistant for docs: Built-in chat helps users explore documentation and ask questions contextually.
• Interactive API playground: Lets users test endpoints directly within the documentation site.
• Analytics and feedback collection: Track which pages are used and gather feedback to improve clarity.

Pricing

Mintlify offers tiered subscription plans:

• A Free (Hobby) plan which includes basic features for individuals
• Pro and Growth plans unlock AI chat, password protection, etc.
• Enterprise options include custom usage-based pricing and premium support.

Pros

• Keeps documentation continuously synced with code
• Intuitive visual editor supports collaboration beyond developers
• Comes with interactive API testing tools
• Usage analytics help refine doc quality

Cons

• More expensive as team size grows; advanced features locked behind paid plans
• Limited customization and content control

4. CodeSee

CodeSee is a code visibility platform designed to help engineering teams document and understand complex legacy systems. It auto-generates live, interactive maps of code structure, service dependencies, and change flow, making large codebases easy to navigate.

Ideal for legacy systems, CodeSee updates documentation in real time and highlights how changes affect other parts of the system. That visibility supports smoother refactoring and onboarding and ensures knowledge stays shared across the team.

Key features

• Auto-syncing code maps: Generates always up-to-date visual maps of file, directory, and service dependencies.
• Interactive review maps: Shows code change impact visually on GitHub PRs, enabling safer refactors and faster reviews.
• Automated service visibility: Discovers and diagrams service interactions, even across microservices or monorepos.
• Code automation templates: Enforce standards, assign reviewers, and generate checklists automatically during refactoring.
• Annotations and embedded notes: Add documentation directly to code maps, and keep it automatically updated as the code changes.

Pricing

CodeSee offers a freemium Community plan for individuals or small open-source projects. Paid Business and Enterprise plans add collaborators, cross-repo visibility, on-prem options, and advanced automation features. 

Pros

• Maps complex codebases automatically for better
• Visualizes refactor impact before merging
• Accelerates onboarding with visual context and auto-updates
• Supports automation of review workflows

Cons

• Enterprise features require paid plans and custom setup
• May become less responsive with very large codebases or extensive visualizations.

5. Tabnine

Tabnine is an AI-powered code assistant that helps teams complete code, generate tests, explain legacy logic, and create documentation, all within your IDE. It's particularly helpful when working in unfamiliar or outdated codebases, as it understands coding patterns and project-specific logic.

It offers a conversational chat and intelligent completions that adapt to your workspace and coding style, making documentation and explanation feel less manual and more contextual.

Key features

• Inline code documentation generation: Create docstrings, comments, and API docs from selected code blocks automatically.
• Legacy code explanations: Ask Tabnine to explain a block of unfamiliar or legacy code for better comprehension.
• Test generation and suggestions: Use Tabnine Chat to generate unit tests aligned with your existing test framework.
• Refactoring assistance: Tabnine can suggest refactors or bug fixes in context without losing behavior fidelity.
• Code completion & chat integration: Combines predictive completions with AI chat for multi-step documentation and code tasks.

Pricing

Tabnine offers three main plans to fit individual developers and enterprise teams:

• Dev plan: Includes full AI chat agents, Jira cloud integration, etc.
• Enterprise plan: Adds advanced AI agents for code validation, private custom models, etc.
• Dev preview / Trial: A free 14‑day trial provides access to the full Dev plan without requiring a credit card.

Pros

• Auto-generates documentation for chosen code segments
• Helps explain complex or legacy code in plain language
• Assists in refactoring tasks with contextual fixes
• Supports offline or on-prem deployment for better security

Cons

• Documentation generation relies on accurate context

Uses a lot of CPU and memory on local installs

6. Codeium (now Windsurf)

Codeium (now Windsurf) is a free AI-powered coding assistant that offers intelligent autocomplete, code explanations, and documentation suggestions. It is mostly helpful for developers working in legacy codebases that lack clear context or comments.

It helps accelerate development by suggesting live doc comments and generating explanations for complex or unfamiliar code blocks.

Key Features

• Context-aware autocomplete: Provides real-time suggestions based on surrounding code and patterns, reducing boilerplate and typos
• Automatic inline documentation: Generates code comments and explanations as you type, helping improve readability in undocumented code
• Legacy code explanations: The tool can analyze unfamiliar blocks of legacy logic and provide human-readable interpretations.
• Multi-language support: Works across more than 70 programming languages, ideal for older or polyglot codebases
• IDE integration: Seamlessly embeds into VS Code, JetBrains, Vim, and other editors for frictionless use

Pricing

Offers flexible plans that range from free individual use to enterprise-grade solutions:

• Free plan: Includes 25 prompt credits, access to all premium models, and more.
• Pro plan: 500 prompt credits per month, optional zero data retention, and up to 5 app deploys/day.
• Teams plan: Includes all Pro features plus centralized billing, usage dashboards, priority support, etc.
• Enterprise plan: Up to 200 seats, includes all Teams features plus additional prompt credits (1,000 each), and more.

Pros

• Unlimited free access for individual developers
• Automatically generates inline documentation and explanations
• Context-aware indexing enables accurate code explanations and doc support.
• Enterprise-ready with audit logging, compliance, and customization features

Cons

• May struggle to accurately explain highly complex or deeply coupled legacy codebases
• Doesn’t retain context across sessions smoothly

7. Workik

Workik is an AI-powered development platform that aids in writing code, debugging, and automating workflows, with a strong focus on code and database documentation. 

It’s particularly effective for teams dealing with legacy codebases or outdated systems due to its ability to generate clear documentation without manual overhead.

Key features

• AI-powered code documentation: Auto-generates code and database documentation from context and schemas based on your project setup.
• Bulk documentation generation: Create documentation for many files or modules in a single batch to save time.
• AI chat assistant: Ask what functions or modules do and get AI-generated explanations instantly.
• Database schema visualizer: Supports SQL/NoSQL schemas and creates ER diagrams for easier understanding.
• Custom documentation layouts: Define and reuse layouts for different file types or extensions across your codebase.

Pricing

• Trial plan: Free access with limited daily request quota and starter AI tokens for evaluation.
• Starter plan: Includes unlimited AI requests, basic token bundle, etc.
• Premium plan: Builds on Starter with higher token limits, increased request throughput, and more.
• Elite plan: Adds priority support, expanded token quotas, advanced usage logs, and enterprise-level features for up to 10,000 flow runs.
• Custom plans: Designed for larger teams or specific needs, with custom token bundles, SSO, dedicated support, and hybrid deployment options.

Pros

• Works well even when code and docs are missing or outdated
• Supports both code and database documentation in one unified platform
• Bulk generation speeds up documentation of large legacy systems
• Customizable layouts offer consistency across varied file types

Cons

• Limited public reviews and adoption data make it difficult to assess real-world performance.
• AI-generated content may need manual review

8. GitHub Copilot

GitHub Copilot is an AI-powered developer assistant deeply integrated into major IDEs and GitHub workflows. It offers suggestions, explanations, and context-aware completions that help teams work efficiently, even in complex legacy codebases.

Key features

• Real-time code suggestions: Generates context-aware autocomplete and code snippets as you type
• Inline documentation generation: Builds docstrings and comments based on surrounding code automatically
• Contextual code explanations: Helps developers understand legacy logic by summarizing function behavior and intent
• Copilot chat support: Enables interactive code Q&A, bug fixes, and unit test generation within your IDE
• Copilot spaces: Organizes code, docs, and specs into a shared context for more accurate responses

Pricing

• Free tier: For individuals; includes up to 2,000 code completions and 50 premium requests per month
• Pro plan: Unlimited completions, Copilot Chat, and access to premium AI models
• Pro+ plan: Offers greater premium request limits, priority features, and access to advanced models

Pros

• Suggestions and documentation are generated as you code, reducing manual effort
• Unlimited completions and premium models on paid plans improve speed and accuracy
• Embedded into GitHub and major IDEs for a seamless developer experience
• Enterprise tiers support governance, billing control, and feature management.

Cons

• GitHub Copilot can sometimes produce inefficient code
• It may not work well with very specific project needs or less common programming languages.

Document legacy code faster with Kodesage

AI tools make documenting legacy code easier, but most were not built specifically for them. Kodesage brings clarity by combining code, tickets, and offline docs into and always up to date, searchable knowledge base.

It helps teams understand complex logic, generate up-to-date documentation, and reduce knowledge silos without manual digging. Whether you’re onboarding, modernizing, or chasing compliance, Kodesage makes the process faster and smarter.

Book a demo now to explore how Kodesage can support your legacy documentation challenges.