19 AI Tools for Technical Writers that Aren’t ChatGPT

Editor’s Note: This post was originally published in April 2025. It has been completely edited and updated for accuracy and comprehensiveness. Please note that the functionalities of the tools listed below may have evolved since the article was published.

Many guides on adding AI to your documentation workflows focus largely on ChatGPT. While ChatGPT is a powerful tool, it’s only one of the many options that can help technical writers. To stay competitive and keep pace with new technology, documentation teams should understand the broader range of AI tools and use cases that can simplify daily work and boost productivity.

Read on to see how technical writers are using AI today. You’ll learn about five categories of AI applications, the top tools in each one, and whether each tool is equipped with a model context protocol (MCP) server for agentic workflows.

How do Technical Writers use AI?

Technical writers use AI to assist them throughout their content operations and automate tasks. AI achieves this without compromising quality, accuracy, or subject-matter expertise.

Today, AI applications are fully integrated into every kind of documentation tool. Used well, AI tools can help technical writers work faster, stay consistent, and produce higher-quality content. Fluid Topics’ Head of Product Knowledge, Rémi Bove agreed, stating that “technical writers can significantly benefit from AI technology to improve their workflows, boost efficiency, and generate top-notch content”. Here are a few ways tech writing teams can put AI to work.

• Speed up content production: Generative AI (GenAI) tools provide a quick way to brainstorm ideas, summarize expert research documents, and prepare documentation outlines. By giving AI the preparation work, tech writers can spend more time on high-value tasks like creating and updating content.
• Reduce translation costs: Teams can render content available in more languages by combining machine-assisted translation with AI-enabled translation. The result is on-the-fly translation of any document into any language the moment a user requests it.
• Enhance content consistency: With the multiplication of authors contributing to documentation, AI tools are useful for reviewing text. They instantly suggest modifications to improve content consistency, tone, complexity, and grammar. This streamlines the documentation workflow for tech writers, optimizing their tasks and improving the time to publication.
• Automate documentation workflows: Agentic AI systems track code changes in repositories and development tools. When they detect an update, they pull the details and draft new documentation, including code examples and clear explanations. The system then sends the draft to subject matter experts for review and tracks approvals in a project management tool.
• Coordinate release notes: Agentic systems orchestrate AI agents to pull release notes and start the generation process when updates appear. They can then retrieve changelog details from GitHub and gather in-product screenshots from design tools to create a single, consolidated release document. Once complete, the system publishes the release notes across multiple channels.

What are the Top AI Tools for Technical Writing Besides ChatGPT?

The top AI documentation tools are divided into 5 categories: AI answer engines, content creation and editing tools, writing optimization and governance tools, code assistants, and technical writing and content publishing tools. If you’re looking to expand your AI tool stack beyond ChatGPT and to automate tasks, you’re in the right place. Read on to discover our top 19 tools and their features.

What Are the Top AI Answer Engines?

To kick off the list, we have some tools that are conversational AI applications, much like ChatGPT. However, the tools below offer unique capabilities beyond natural language generation that distinguish them from the rest.

1. Gemini

Gemini is Google’s LLM that powers its conversational AI assistant (formerly called Bard). It can generate text, video, and images. It draws information from both its LLM and Google results to answer user questions. Gemini is the default answer engine available in Google workspaces and Google products.

Key features:

• Deep Research: This feature allows users to generate a research plan, crawl hundreds of sources, and produce a cited report the user can then refine. This is useful for background research before writing, such as API landscape overviews, competitor doc audits, and compliance summaries.
• Canvas: This is Gemini’s dedicated workspace for content collaboration. Users can also integrate their Deep Research and let Canvas transform it into documentation, diagrams, or other helpful content.
• Video Creation: Gemini Omni allows teams to create and edit videos directly from natural language prompts. This tool complements Google’s existing Nano Banana AI image generator. This can bring technical documentation to life with walkthroughs and interactive guides.

2. Perplexity AI

Perplexity is an AI-powered search engine that transforms the experience of finding and interacting with knowledge. It calls itself a “Swiss Army knife for information discovery and curiosity,” using an algorithm that pulls from the latest online sources to deliver accurate, detailed responses.

Key features:

• Internal Knowledge Search: For enterprise accounts, administrators can add up to 500 company files (XLSX, PPTX, DOCX, PDF, or CSV) to supplement Perplexity’s knowledge from public internet sources. These retrieval-augmented generation (RAG) searches combine insights from the web and internal documentation to improve answer relevance and decision-making.
• Custom Pages: This tool lets users turn subjects into formatted articles, guides, and reports. After adding a search topic, Perplexity instantly generates an article which users can then customize and edit to reflect the information they want to share and the tone they want to use. They can then add their own images before sharing the content with their audience.
• Focused Results: Perplexity’s Focus feature allows users to filter results by type of source to save time and improve relevance. The Focus options include All, Social, Video, Writing, Academic, and Math. As a result, users get targeted results.

Which AI Content Creation and Editing Tools Support Technical Documentation?

AI content creation platforms help technical writers to take their documentation to the next level with multimedia content that engages users in new ways. No need to become a graphic design expert; these tools are user-friendly with high-quality results.

3. Canva

With over 30 billion designs created by over 220 million monthly active users, Canva is a global leader in online design. While not solely an AI tool, Canva’s Magic Studio offers several AI-powered tools to enhance teams’ creative endeavors, creating professional designs without advanced graphic design skills.

Key features:

• Photo to Mock-up: This tool allows users to upload images and get instant mockup templates showing various layouts and image placements. For tech writers, this simplifies the process for creating engaging user guides and automates time-consuming activities so they can focus on writing.
• Magic Resize: Users can easily convert content into new formats, languages, and dimensions to ensure documentation is available for all users and device types. This tool allows users to resize visual content for any channel and transform entire pieces of content, say from a detailed maintenance guide to a help desk article.
• Video Highlights: This feature turns long explanatory videos or walkthroughs into short, engaging clips that you can integrate into each user manual step for a better user experience. Canva’s video highlights do just this, suggesting snappy clips to extract from full-length footage.

4. Filmora

Filmora is an easy-to-use tool that helps teams create video content, even without production experience. Its AI features and simple controls let creators of any skill level turn ideas into polished, professional videos. Tech writers can use Filmora to record live demos of complex maintenance tasks or create clear, step-by-step installation guides for customers at home.

Key features:

• AI Text Editing: This AI text tool generates automatic captions based on a video’s audio. If there are any mistakes or customizations needed, users can easily edit the text. And to serve international clients, teams can seamlessly translate captions and audio with voice cloning to maintain consistency.
• Smart Short Clips: With smart clips, users repurpose long, one-shot clips into several short videos with the power of AI. Automatically extract key highlights and add voiceovers to enhance value. Once the video is cut up into smaller pieces, users can trim, edit, and rearrange individual clips to customize the final deliverable.
• Background Audio Removal: This tool is key for tech writers who want to integrate videos into documentation, but who need to film on-site interventions or other procedures taking place in noisy environments. They can easily remove the background noise from video or audio files to create clear, quality audio.

5. Snappify

Snappify helps users turn technical content into clear, engaging visuals. Companies can create polished code-based presentations and infographics that make complex ideas easier to grasp. The platform lets you annotate and highlight code, organize reusable snippets into a library, and more. With this platform, even complex documentation with code is easy to understand.

Key features:

• AI Explanations: This GenAI feature allows users to automate the creation of code block explanations. That way, they don’t have to prepare the commentary themselves. For explanations that need more context, writers get an accurate first draft they can edit to add the necessary specifics.
• Custom Annotations: Users can add context and explanations to code blocks to help end users better understand your documentation. Snappify offers a rich-text editor. It allows users to add elements like arrows, ellipses, highlights, and blurred boxes to specific parts of the code.
• Premade Templates: Users can start designing and customizing instantly by simply choosing a premade template that aligns with their goals and company branding. From there, users can easily add images, elements, and multiple code snippets to the template.

6. Napkin AI

Napkin is a visual generation tool that quickly turns written explanations into diagrams. Once generated, teams can adjust and polish the image according to their needs and style guidelines. Once completed, the visuals can be exported as .ppt, .png, .pdf or .svg.

Key features:

• Team Collaboration: Napkin includes powerful collaboration tools. With Teamspace, users can manage members in a shared workspace. Real-time editing lets multiple people update an image at the same time. Built-in highlighting also allows teammates to leave comments and feedback directly on text and visuals. For technical writers, this closes the gap between writer and SME review.
• Napkin Slides: This beta feature turns real presentation text into slides. For each slide, it offers several ways to present ideas. After it generates the deck, everything is editable directly on the slide or through the agent. This is useful for tech writers who get asked to repurpose docs into release-ready decks, onboarding walkthroughs, or internal training slides.
• Effects: The Effects feature turns Napkin visuals into studio-quality images in the aesthetic of the user’s choice. To choose the aesthetics, users can choose from preset options or describe the look they want in natural language. For documentation, this creates customer-facing diagrams while keeping the underlying content technically accurate.

7. Scribe

Scribe is a screen-capture and process documentation tool that automatically creates step-by-step guides. It records clicks, keystrokes, text entries, and navigation, then uses AI to organize everything into a clear, annotated SOP with screenshots in minutes.

Key features:

• Capture: Scribe automates workflow docs, generating content for teams’ most common processes. This feature will soon flag outdated documentation when workflows change. For tech writers, this removes the tedious act of working with an SME to screen-record and document every step. It’s especially useful for internal SOPs and tool walkthroughs that rarely get written.
• Workflow Context Layer: First, the system captures every workflow and variation. Then, teams can use this layer to set up AI agents that can execute actions, automate processes, and monitor workflow data.
• Scribe Optimize: The system observes each team’s workflows and tools to capture operational context. It uses live data to identify new automation candidates and make adjustments to existing workflows.

What are the Top AI Writing Optimization and Governance Tools?

Everyone makes typos and writes sentences that sound great in their heads but need clarity once on paper. This is becoming even more complex with the rise of AI-generated content, which needs extra review to check terminology, grammar, tone, and more. Leave these editing and validation tasks to AI writing assistants that run real-time checks and sentiment analyses to improve writing.

8. oXygen AI Positron

oXygen’s AI Positron Assistant is an add-on solution for those already using oXygen XML. It is aimed at supporting technical authors throughout the content production process. This AI tool streamlines technical writing by helping teams generate, rework, research, and summarize content in addition to various AI assistance features that enhance the writing and review processes.

Key features:

• AI Edits and Fixes: Writers will streamline the content review process with Oxygen’s AI-Fix tool, which identifies and modifies validation issues. This solution also checks for grammar and spelling errors, offering smart solutions to improve and harmonize text. With this feature, you will get to the publishing phase faster so that customers can benefit from your documentation sooner.
• Agentic Chat: Oxygen users can harness the power of agentic AI to orchestrate actions. This includes everything from creating new files from Word, PDF, or image files, to implementing project-wide modifications.
• Vision Model Support: Oxygen’s AI Positron Assistant supports Vision models to allow users to read and understand images. This supports tech writers by optimizing DITA content creation as it allows them to precise the context, prompt, and images when generating drafts.

9. Markup AI

Markup AI (formerly Acrolinx) is an AI-powered content governance solution that ensures content adheres to a team’s defined standards for quality, consistency, and tone. From specific terminology to clarity, inclusivity, and tone of voice, Markup AI ensures AI-generated content passes all quality checks based on an organization’s writing guidelines.

Key features:

• AI Writing Assistant: This GenAI tool creates, summarizes, and expands on text to help facilitate the content writing process. Plus, every suggestion is crafted in line with a company’s unique content standards.
• AI Visibility Agents: These beta agents scan content during the content creation process directly within content authoring tools. They then suggest ways to optimize content to be found and cited by LLMs.
• Compliance Guardian Agents: These AI agents eliminate regulatory risk and protect brand reputation. They automate content control and compliance checks across three categories: verifiable claims, promissory language, and terminology.

10. Congree UCC

Congree UCC is a platform that helps companies create unique corporate content. This solution proofreads text and provides real-time documentation compliance checks. That way, you ensure all of your content aligns with company specifications and guidelines. The goal is to help teams develop more quality-assured text, faster.

Key features:

• AI Terminology Development: This feature uses GenAI to help brainstorm term proposals and develop a terminology database for technical writers. The databases include definitions, synonyms, and links to help documentation teams build vocabularies.
• GenAI Text Suggestions: The platform’s Authoring Memory feature combines GenAI and linguistic intelligence technology to provide text suggestions that allow writers to reuse past, approved text formulations. Content reuse reduces production time and costs for both writing and translating documentation.
• Language Model Customization: This solution provides teams with various assets from style guides to vocabularies, Authoring Memory to suggest text, and text corrections. Congree UCC promotes these resources to help companies train and customize language models for their internal writing specifications. This renders AI-generated text more accurate, requiring fewer adjustments.

11. Grammarly

Grammarly is a widely used writing assistant that checks grammar issues, typos, and opportunities to improve clarity in real time wherever the user is writing. You can tailor its suggestions to match your preferred style and tone. It also lets documentation teams add approved technical terms to a custom dictionary, so important terminology isn’t marked as a mistake.

Key features:

• Grammarly Go: With this AI-powered feature, writers can select a section of text and a pre-defined AI prompt (e.g., improve this text, make it sound more professional, simplify this text, etc.). Grammarly then reworks the paragraph with its own ideation of how to adjust the text according to the selected prompt.
• Real-Time Text Suggestions: Grammarly checks content and suggests fixes for spelling, punctuation, and grammar errors. It also recommends style and tone changes while authors write. When technical writers fix mistakes as they write, the first draft needs less editing. This saves time later in the workflow.
• Readability Scores: This feature provides writers with a reading level score that indicates how easy or difficult their text is for end users to understand. It determines the score by looking at sentence length, word choice, and global readability. This is a critical insight for technical writers who need to create documentation for different user types, each with different levels of technical expertise.

12. DeepL Write

DeepL expanded their offer from DeepL Translator — a widely-used tool — to add a writing assistant. The feature, DeepL Write Pro, refines writing with AI-powered suggestions and edits. It also reworks content for new formats, helping writers turn the content of emails, reports, and presentations into documentation.

Key features:

• Automatic Text Improvement: Writers get AI-powered text enhancement suggestions to upgrade their clarity and quality. Plus, to seamlessly integrate this into writing workflows, teams can implement DeepL Write into different writing platforms, including Google Workspace and Microsoft 365.
• Customized Communication Style: This product offers several options for writing styles (e.g., simple, business, academic, casual) and tone (e.g,. enthusiastic, friendly, confident, diplomatic). This allows authors to tailor writing suggestions to their style guidelines.
• Best-In-Class Security: DeepL Write is GDPR, ISO 27001, and SOC 2 Type II compliant. By adhering to leading security and data privacy standards, writers can rest assured that their confidential content will remain protected. Additionally, the product specifies that it never stores data without consent or uses data to train its AI models.

What are the Best AI Code Assistants for Technical Writers?

AI coding assistants are tools built on LLMs that use AI to support software engineering work such as generating and reviewing code. For technical writing, they can read real code, diffs, and API specifications to draft accurate documentation. They also speed up repetitive tasks like producing API references, creating code examples, and keeping style and terminology consistent across large documentation sets. As a result, technical writers can spend more time on structure and review rather than writing first drafts from scratch.

13. Claude Code

Claude Code is a subproduct of Claude, an AI assistant developed by Anthropic. Claude Code allows teams to work with Claude directly in their codebases. There, they can build, debug, and deploy code directly from their terminals, IDE, Slack, and more.

Key features:

• Native Integrations: Claude Code includes built-in extensions for VS Code (plus Cursor and Devin Desktop) and JetBrains IDEs. It also connects with GitHub, GitLab, and command-line tools, so developers can handle their entire workflows from the terminal, including reviewing issues, writing code, running tests, and submitting pull requests. This supports a docs-as-code setup where docs live in the same repository and workflow as the code.
• Routines: A routine is an automation that developers configure once and then let run via an API call or in response to an event. These routines ship with access to specific repositories and connectors, so developers can package automations and let them run on a schedule. This is useful for keeping docs from going stale whenever an API spec or config schema changes, rather than relying on someone remembering to loop in docs.
• Dynamic Workflows: Developers can build workflows that tackle complex tasks by running dozens or even hundreds of sub-agents in parallel, with automatic checks and opportunities for human review. Work that used to take a whole quarter to finish can now be completed in just days.

14. GitHub Copilot

GitHub Copilot is an AI coding assistant that helps developers write, understand, refactor, and debug code quickly. It integrates directly into development environments to provide a seamless workflow.

Key features:

• Digital Workspace Integration: Developers can assign tasks to Copilot directly from a Slack or Teams conversation. The agent pulls context from the conversation, including decisions, links, and code, to accelerate small fixes and tedious tasks, so developers can focus on more complex issues.
• Next Edit Suggestions: Based on a developer’s recent edits, next edit suggestions predict where the next change will happen and what it should be. Suggestions can cover anything from a single character to multiple lines, depending on the size of the change.
• Resolve Merge Conflicts: Developers can resolve Git merge conflicts by creating an agentic flow in the VSC editor. The AI receives the merge base and changes from each branch as context. (Note: This feature is still experimental at the time of publication).

15. Cursor

Cursor is an AI coding agent that integrates directly into software development workflows. Developers can direct the agents to search across a codebase, edit files, run terminal commands, and execute multi-step programming tasks from natural-language instructions.

Key features:

• Codebase Understanding: Cursor AI learns your entire codebase regardless of size or complexity so it can reason across files and modules. It indexes your local project to understand your code, libraries, and dependencies, then uses that context to deliver accurate, project-specific suggestions. For API docs, a writer could ask “what does this function actually do” and get an answer grounded in the current codebase rather than an outdated spec or a guess.
• Design Mode: Design Mode helps developers guide agents using visual prompts. They simply have to click on an element in the Agents Window browser and either draw or describe the change by voice. Cursor captures the right context and updates the code so they can move on to the next task.
• Debugging: Debug Mode helps developers reproduce and fix hard-to-diagnose bugs. Instead of jumping straight into code changes, the agent forms hypotheses, adds logging, and uses runtime data to isolate the root cause before applying a focused fix.

Which Technical Writing and Content Publishing Tools Do Documentation Teams Need?

Documentation teams need writing and publishing tools like CCMSs and Product Knowledge Platforms to produce and deliver technical documentation. The above tools are great for getting started, brainstorming, working with subject matter experts, and creating multimedia content. The following tools for creating and publishing structured technical documentation are at the heart of a documentation team’s core missions.

16. Fluid Topics

Fluid Topics is the leading AI-powered Product Knowledge Platform (PKP) that aggregates and unifies all product and technical knowledge, no matter the initial source or format. Whether it’s structured DITA, product PDFs, Word files, HTML, Markdown, OpenAPI specs, or beyond, everything is brought together into one centralized repository. Once consolidated, Fluid Topics dynamically delivers the most relevant content to any digital channel, device, or application, tailoring the experience to match users’ contexts, needs, and environments.

Key features:

• Seamless Content Aggregation: Coordinating content from multiple authoring tools with varying output formats is often tedious. Fluid Topics streamlines this process by automatically harmonizing diverse content types into its platform, eliminating the need for manual reformatting and freeing up valuable time for tech writers.
• Continuous Publishing: Static documentation is outdated, rigid, hard to update, and slow to adapt. Make the switch to dynamic content with continuous publishing, which lets teams automatically publish approved content anytime. Continuous publishing ensures tech writers can always keep users informed with the latest product updates without relying on the IT department.
• Consistent Content Delivery Across Platforms: As content consumption spreads across an ever-growing number of endpoints, technical writers face the challenge of delivering the right information in the right format to each one. Fluid Topics makes it easy to deliver consistent, accurate information to any channel, be it a documentation portal, chatbot, website, or support channel. Users get the information they need exactly where and when they need it.

17. Paligo

Paligo is a leading Component Content Management System (CCMS) that offers topic-based authoring with single-sourcing documentation reuse. This Docbook-based solution is a tech writer’s favorite for developing technical documentation, training support, policies and procedures, and other product knowledge content.

Key features:

• Structured Authoring: This tool keeps technical writers focused on creating content without worrying about layout or formatting. Paligo offers predetermined components to create structured content, facilitate documentation reuse, enhance consistency, and lower costs.
• Content Reuse: An essential CCMS feature, content reuse means tech writers create and have access to a library of their pre-approved content components. These content blocks are available in multiple formats for easy use in any document. Authors don’t need to start from zero for each piece of content.
• AI Assistant: This tool is built into the Contributor Editor. The AI Commands offer tech writers targeted suggestions to improve, shorten, lengthen, simplify, or summarize content. The Generate feature uses OpenAPI to create new content on any topic.

18. Heretto

To conclude our list, Heretto is another top CCMS and a popular choice for information development teams across industries. Their DITA-powered content operations stack helps technical writers create documentation with features like content reuse, version control, and real-time collaboration.

Key features:

• Structured Content Lifecycle Management: Teams use this tool to manage the full scope of their content production, thanks to this tool’s intuitive interface. The platform is cloud-based, making it an ideal choice for large-scale collaboration. Finally, structured content writing and history logs help teams manage documentation.
• Content Governance: Heretto makes it easy for teams to produce content that adheres to industry regulations and internal documentation standards with compliance and regulation checks. This tool offers data security with its commitment to SOC Type II compliance and version control management.
• AI Copilot: Etto is Heretto’s AI-powered assistant designed to optimize content creation with intuitive features. Etto combines deep DITA expertise with writing and summarizing text or recommending content edits to scale content production, improve content and brand consistency, boost productivity, and foster customer loyalty.

19. Mintlify

Mintlify is an AI-native knowledge platform for AI agents. In other words, it creates structured outputs for AI agents and clear documentation for people. It automatically generates llms.txt and skill.md, and it runs an MCP server so tools like Cursor and Claude Code can query the documentation directly.

Key Features

• Automations: Documentation teams can automate content maintenance with AI agents that respond to scheduled times or GitHub and GitLab repository pushes. The agent reads the project content, then follows preset prompts to update content.
• AI Chat Assistant: The assistant answers user questions about documentation, cites sources, and generates examples on demand. Users quickly get answers without having to search through documentation.
• Integrations: Mintlify offers native connections to key workplace solutions like Slack, Notion, Jira, Confluence, and more. This allows documentation teams to pull live context from their discussions and collaborations within these tools to make internal knowledge available as documentation.

Note: There are many other top-of-the-line CCMSs available to choose from, including Madcap IXIA CCMS, Tridion Docs, Author-it, Componize, DITAToo DITA CCMS, and Bluestream’s XDocs DITA.

Conclusion

We recommend building your tech stack from this “best-of-breed” list of AI-enabled tools. As a result, your technical writing team will take its documentation to the next level. Harnessing these AI tools will optimize documentation workflows, enhance the user experience, and boost business ROI.