12 Software Documentation Tools Worth Comparing in 2026

Software documentation tools help teams create, organize, and publish technical content, from developer APIs to internal wikis to customer help centers. The right one depends on who’s writing it, which is why comparing all of them on one list rarely helps.

A support team spends three days evaluating a Git-native tool, only to realize nobody on the team knows what a pull request is. An engineering team picks a simple editor, then hits a wall the first time they need to auto-generate an API reference.

Both mistakes come from treating “software documentation tools” as one category, when it’s really three: developer-first, API-first, and non-technical. In this blog, I’ll walk you through 12 tools worth considering in 2026, sorted by which lane they actually serve.

What Is Software Documentation?

According to the Stack Overflow Developer Survey 2025, 68% of developers reach for technical documentation first when learning something new, ahead of AI tools (44%) and any other resource.

It shows up in several forms:

• API documentation: Endpoint references, request and response specs, SDK guides for developers building on top of a product
• Internal engineering documentation: Architecture docs, onboarding runbooks, and technical design notes for teams maintaining the codebase
• User documentation: Manuals, troubleshooting guides, and installation instructions for end users
• Customer-facing help content: FAQs, how-to articles, and self-service knowledge bases for support teams

A concrete example: API documentation for a payment SDK lists every available function, the parameters it accepts, and a working code sample showing how to call it. That’s different from user documentation for the same product, which walks a merchant through connecting their account, with none of the function-level detail a developer needs.

Not every tool on a “software documentation” list solves the same problem, which is exactly why the lane you’re building for matters more than the feature checklist.

Top 12 Software Documentation Tools Compared

Once you know which lane you’re in, developer-first, API-first, or non-technical, the next question is which specific tool fits best. Here’s how all 12 stack up before we get into the details on each.

Now let’s look at what actually sets each of these 12 apart, starting with the four built for accessible, hybrid, or general-purpose documentation.

1. ProProfs Knowledge Base: The Easiest Customer Support Help Center & Internal Employee Knowledge Base in One

Most software documentation tools force a choice between developer-first and non-technical workflows. What stood out to me about ProProfs Knowledge Base was how quickly a mixed team could start publishing anyway. I could manage customer-facing help, internal knowledge, and technical documentation from the same account, which meant fewer tools to maintain and less admin work.

The biggest time-saver was content creation. AI Writer turned a rough prompt into a workable first draft in seconds, so I spent less time outlining and more time refining the actual content. If the search still didn’t resolve a reader’s question, I could move them directly into ProProfs Chat instead of sending them to another support channel.

I also liked that contributors didn’t need Markdown, YAML, or Git to make updates. Support, product, and subject-matter experts could contribute directly, which kept routine documentation changes from getting stuck with engineering.

Pros:

• No-code editing lets support, product, and subject-matter experts contribute without learning Git, Markdown, or YAML
• AI Writer cuts the time spent creating first drafts from a short prompt
• AI Search Assistant returns direct answers to natural-language questions, helping readers find information with less digging
• AI Insights & Reports surfaces failed searches, broken links, and content gaps before they turn into repetitive support work
• One account manages public help content, internal knowledge, and technical documentation, with permissions, SSO, and a REST API
• Content publishes in 90+ languages, with 100+ ready-to-use templates to start from

Cons:

• No downloadable or on-premise version
• No dark mode
• A visual-first workflow may be less suitable for engineering teams that want docs to live entirely in code repositories

User Rating: 4.7/5 (Capterra)

Pricing: Free plan available with all premium features, up to 25 pages. Paid plans start at $49/author/month.

Bob Bednarz, L&D Manager at Smokeball, says the client-facing knowledge base his team built with ProProfs helped increase page views and improve engagement rate. See how they did it.

Read The Full Case Study

2. GitBook: Hybrid Teams Needing Both Git Workflows and Visual Editing

I used GitBook, where developers, product managers, and support staff all needed to contribute to the same documentation without one group blocking the other.

Its defining feature for me was bidirectional Git Sync. My engineers wrote Markdown in pull requests through GitHub or GitLab, while non-technical contributors edited the same content through a visual, browser-based editor, and both workflows updated the same source. On the API side, it generated reference pages directly from our OpenAPI specification, rendered with an interactive playground.

It also treated AI agents as first-class readers of our docs. It generated an llms.txt file so language models could parse our content properly, and exposed MCP server analytics showing me which AI agents were querying our documentation and where they were hitting gaps.

Pros:

• Bidirectional Git Sync lets engineers work through pull requests while non-technical contributors edit the same documentation visually
• Git-based review stays intact for teams that already manage documentation changes alongside code
• AI Assistant, AI Agent, llms.txt, and MCP-related capabilities make the documentation more useful to both readers and AI systems
• OpenAPI support can generate interactive API reference content without requiring a separate publishing platform
• SAML SSO and access controls make it easier to scale the same workflow across larger teams

Cons:

• Git workflows still introduce a learning curve for contributors who need to work in the repository
• The pricing model can become expensive as both site and user costs increase
• No native SDK generation for teams that need client libraries alongside API docs
• Some advanced governance and access features are aimed at higher-tier plans

User Rating: 4.5/5 (Capterra)

Pricing: Free plan available. Premium is $65/site/month plus $12/user. Ultimate is $249/site/month plus $12/user.

3. Confluence: Teams Already Deep in the Atlassian Ecosystem

I found Confluence a collaborative workspace built for teams that document, plan, and communicate together, with real-time editing and structured spaces sitting alongside traditional pages.

Rovo, Confluence’s AI layer, drafted documents, summarized long pages, and helped me find information across connected tools. I found it could surface when a page had likely gone stale and propose an edit, but I still had to trigger that action myself rather than it happening automatically.

Deep integration with Jira turned out to be the platform’s real differentiator for me. My requirements docs lived right next to the Jira tickets they described, so engineering and product weren’t jumping between two disconnected systems.

Pros:

• Deep Jira integration keeps requirements, decisions, and delivery work connected, reducing context switching between tools
• Rovo can speed up drafting, summarization, and information retrieval across connected Atlassian content
• Spaces, nested pages, labels, and macros give large teams flexible ways to organize internal documentation
• Granular permissions support space-, page-, and group-level access for controlled collaboration
• Real-time editing, comments, whiteboards, and databases make it well suited to collaborative product and operations work

Cons:

• Search and navigation can become harder to manage as spaces grow
• Large deployments usually need active governance to prevent duplicate or poorly organized pages
• No Git-native authoring model for teams that want documentation reviewed like code
• Best suited to internal collaboration rather than specialized API reference publishing

User Rating: 4.5/5 (Capterra)

Pricing: Free plan available for up to 10 users. Standard plan starts at $5.42/user/month.

4. Notion: Informal Internal Wikis and Lightweight Team Knowledge

I liked that Notion’s block-based structure let me build exactly the layout I needed instead of working inside a fixed template. Databases, boards, and document pages all lived in the same workspace, so I could build a wiki, track a project, or document a process without switching tools.

Notion AI, bundled into the Business tier and above, handled drafting, summarizing, and search directly inside my pages. The same underlying data rendered as a table, kanban board, or calendar depending on what I needed to see.

Pros:

• Block-based pages let teams combine documentation, databases, boards, and project tracking in one workspace
• Database views can reuse the same information as tables, boards, calendars, or galleries without duplicating content
• AI features can accelerate drafting, summarization, and search inside the workspace
• Real-time comments and version history support fast-moving, collaborative internal knowledge
• Integrations with tools such as Slack, GitHub, and Google Drive help keep documentation connected to everyday work

Cons:

• No Git-native workflow for engineering-led documentation
• No dedicated API documentation or OpenAPI generation workflow
• Information architecture can become inconsistent without active ownership
• Better suited to lightweight internal knowledge than large, tightly governed documentation portals

User Rating: 4.7/5 (Capterra)

Pricing: Plus plan starts at $10/member/month (billed annually).

5. Docusaurus: Open-Source Projects Needing Full Control Over a Self-Hosted Site

I picked Docusaurus, the open-source documentation framework maintained by Meta, built on React with Markdown and MDX authoring. It’s the same tool behind documentation for projects like React Native, Redux Toolkit, and Prettier.

Because it’s built on React, I got complete control over the frontend, custom components, layouts, and interaction patterns were all fair game for me. The tradeoff was that I had to manage hosting, deployment, and editorial workflows myself rather than relying on a managed platform to handle it.

Pros:

• React-based customization gives engineering teams full control over layouts, components, and documentation-site behavior
• Built-in versioning makes it easier to maintain documentation for multiple product releases in parallel
• A large plugin ecosystem extends search, analytics, internationalization, and other site capabilities
• Static HTML generation delivers fast pages that can be hosted on almost any infrastructure
• Open-source licensing removes platform fees for teams willing to manage hosting, deployment, and maintenance themselves

Cons:

• No visual editor for non-technical contributors
• No built-in AI authoring or search layer
• Analytics, review workflows, and many publishing features depend on plugins or custom setup
• Hosting and maintenance consume engineering time

User Rating: Not independently rated (open-source)

Pricing: Free and open source. Costs come from hosting and engineering time, not the software itself.

6. GitHub: Teams That Want Docs Living Directly Alongside Code

GitHub isn’t a dedicated documentation platform, but I found its version control and Markdown support made it a genuine option for keeping documentation in the same repository as the code it described.

README files served as my front-line documentation for most projects, and GitHub Pages or Wikis hosted more extensive docs when I needed them. My team could track changes, open pull requests, and manage documentation contributions the exact same way we managed code.

Pros:

• Documentation can live and version in the same repository as the code it describes, reducing drift between the two
• Pull requests, reviews, and branching let teams manage documentation changes with the same workflow they already use for code
• GitHub Pages and integrations with generators such as Jekyll, Docsify, and MkDocs can turn repository content into a published site
• GitHub Actions can automate documentation builds and deployments after changes are merged
• The existing GitHub ecosystem keeps setup and contributor onboarding simple for engineering teams already working there

Cons:

• Built-in Wikis and README files are basic compared with dedicated documentation platforms
• Steep learning curve for non-developers
• Customer-facing documentation usually needs additional tooling for search, navigation, and presentation
• Large documentation libraries can become difficult to manage without a generator or separate docs framework

User Rating: 4.8/5 (Capterra)

Pricing: Free plan available. Team plan is $4/user/month for the first 12 months. Enterprise starts at $21/user/month for the first 12 months.

Want a head start? Use this software documentation template to skip the blank-page setup 

Use This Template

7. Read the Docs: Docs-as-Code Teams Using Sphinx or MkDocs Needing Automated Builds

I used Read the Docs to connect to my Git repository and treat documentation like code, building, previewing, and hosting it automatically so my engineering team didn’t have to run its own docs infrastructure.

Every pull request I opened got a live preview build with a visual diff against production, so my team reviewed rendered output instead of raw markup before merging. It’s hosted open-source documentation since 2010, with projects like Flask, Jupyter, and Godot Engine running on it today.

Pros:

• Automated builds on Git pushes remove much of the manual hosting and deployment work from a docs-as-code workflow
• Pull-request preview builds let teams review rendered documentation before merging changes
• Native support for Sphinx, MkDocs, and Docusaurus fits common documentation toolchains without forcing a new authoring model
• Versioned builds map naturally to branches and releases, making multi-version documentation easier to maintain
• llms.txt and agent-oriented capabilities help make published documentation easier for AI systems to consume

Cons:

• Requires contributors to be comfortable with Git-based authoring
• No native visual editor for non-technical teams
• Less suitable when support or product teams need to publish without engineering help
• Private or commercial use moves teams onto paid plans

User Rating: Not independently rated (open-source)

Pricing: Community plan is free for open-source projects. Business plans start at $50/month for private repositories and commercial use.

8. MkDocs: Small Technical Teams Wanting a Lightweight, Self-Hosted Docs Site

I picked MkDocs, a fast, simple static site generator built specifically for project documentation. I wrote documentation in Markdown and configured it through a single YAML file, then built it into a static HTML site with one command.

I paired it with the Material for MkDocs theme, which added navigation, search, and a more polished look on top of the two built-in themes. Most advanced functionality I needed came through community plugins rather than built-in features.

Pros:

• A single YAML configuration file keeps setup straightforward for developers already comfortable with Markdown
• The live-reloading development server speeds up writing by showing changes as they are made
• Material for MkDocs and the wider theme/plugin ecosystem can add polished navigation, search, analytics, and design
• Static HTML output is fast, portable, and inexpensive to host on services such as GitHub Pages or Amazon S3
• Open-source licensing keeps software costs at zero for teams prepared to manage plugins, hosting, and deployment themselves

Cons:

• No visual editor for non-technical contributors
• Advanced features often require third-party plugins or themes
• No built-in AI, editorial workflow, or managed analytics layer
• The team remains responsible for hosting, deployment, and plugin maintenance

User Rating: Not independently rated (open-source)

Pricing: Free and open source. Costs come from hosting, not the software.

9. Mintlify: AI-Ready API Documentation for Fast-Shipping Startups

I brought in Mintlify because my documentation changed as often as my product did, and I wanted that documentation to serve both human readers and AI agents equally well.

I kept content in Git as MDX files, and sync ran in both directions: I could push a change through a pull request, or edit the same page through the browser, without either workflow overwriting the other. Keeping docs from drifting out of date used to be a manual, easy-to-skip task for me; Mintlify’s Workflows agent instead watched code changes, drafted the documentation update itself, and opened a pull request for me to review.

Pros:

• OpenAPI and AsyncAPI support can generate reference pages automatically, reducing manual API-reference work
• Workflow automation can draft documentation updates from code changes for human review, helping docs keep pace with releases
• Git-based authoring and browser editing can coexist, so technical and non-technical contributors are not forced into one interface
• Preview deployments, comments, suggestions, and mentions make review easier before documentation changes go live
• AI traffic analytics can show how AI systems use the documentation and where they encounter gaps

Cons:

• Pricing rises sharply from the free tier to the Pro plan
• MDX authoring can still be a barrier for non-technical contributors
• Designed more for developer documentation than broad internal knowledge management
• No clearly stated self-hosted option for teams that require on-premise deployment

User Rating: 4.6/5 (G2)

Pricing: Hobby plan is free. Pro starts at $450/month with annual billing.

10. ReadMe: Interactive, Developer-Friendly API Reference Hubs

I used ReadMe to turn a static API spec into something my developers could actually test, not just read, which was the core problem I needed solved.

I uploaded an OpenAPI spec and it became a live reference where a developer on my team could run real API calls using their own API keys, directly from the documentation page, instead of switching to a separate tool like Postman just to try an endpoint. My contributors could also work on branches without publishing changes immediately, so a draft didn’t go live before it was reviewed.

Pros:

• Interactive API reference lets developers test requests from the documentation, reducing the need to switch to a separate API client
• Branching keeps draft documentation isolated until it has been reviewed and is ready to publish
• Usage analytics show popular endpoints and error patterns, helping teams see where developers may need better guidance
• GitHub and GitLab integrations support repository-based review alongside the publishing workflow
• Reusable content blocks and AI-assisted linting reduce repetitive updates and help keep larger documentation sets consistent

Cons:

• The jump from free to paid plans can be significant for smaller teams
• Collaboration and privacy features become more useful on higher tiers
• Best suited to API and developer documentation rather than broad internal knowledge bases
• Teams with simple static API references may not need the full platform

User Rating: 4.3/5 (Capterra)

Pricing: Starter plan is free. Pro is $250/month billed annually. Enterprise is custom-priced.

11. Redocly: Strict OpenAPI Governance Across Many APIs

I picked Redocly not to write documentation, but to keep it consistent and correct across the many teams at my organization each publishing their own APIs under one company.

A CLI checked our OpenAPI specs against our own style rules before anything got published, catching inconsistencies before they reached a reader. On the reader-facing side, Redoc, the open-source renderer at Redocly’s core, turned a spec into a clean, responsive reference page automatically for me, without anyone manually building a documentation site around it.

Pros:

• CLI linting checks OpenAPI specifications against organization-specific rules before publication, catching consistency issues early
• Redoc can turn API specs into reader-friendly reference documentation without manually building each page
• CLI workflows fit naturally into CI/CD pipelines, letting governance checks run as part of the existing release process
• Mock servers let developers simulate API behavior before production endpoints are available
• Open-source Redoc provides a low-cost starting point, while enterprise controls add SSO and RBAC for larger organizations

Cons:

• Narrow focus on API documentation and governance
• Teams producing product guides or internal wikis will likely need another platform
• Product packaging and pricing can take time to evaluate across the broader Redocly suite
• A CLI-centered workflow is less approachable for non-technical contributors

User Rating: Insufficient review volume to report.

Pricing: Pro is $10/seat/month. Enterprise is $24/seat/month.

12. Swagger UI: Free, Automatic API Reference From an OpenAPI Spec

I used Swagger UI to take a static OpenAPI or Swagger specification and turn it into a documentation page my developers could actually click through and test, rather than a plain text file they had to read line by line.

Every endpoint, parameter, and response the spec defined rendered visually and color-coded by request type, and a built-in “Try it out” button sent a real request and showed the real response, directly in the browser. It’s entirely open source, so I didn’t need to buy a license just to start using it.

Pros:

• Automatically turns OpenAPI endpoints, parameters, schemas, and responses into a readable interactive reference
• The built-in “Try it out” experience lets developers send requests directly from the documentation page
• It can run locally or in a wide range of hosted environments with very little infrastructure overhead
• Open-source licensing and full source access keep costs low while allowing teams to customize the presentation
• Support for Swagger 2.0 and OpenAPI 3.x makes it useful across both older and newer API specifications

Cons:

• Large specifications can become difficult to navigate and slower to render
• Default presentation is more utilitarian than newer developer-portal products
• No content layer beyond what is defined in the API specification
• An incomplete or outdated spec produces incomplete or outdated documentation

User Rating: 4.5/5 (G2)

Pricing: Free and open source. SmartBear’s commercial SwaggerHub layer is available on request, with pricing not publicly listed.

How Did I Evaluate These Tools?

Choosing the wrong documentation tool costs more than the subscription, so here’s what I actually checked before ranking any of these 12.

• User Reviews and Ratings: Older write-ups get stale fast, so G2 and Capterra gave me verified feedback, and I cross-referenced pricing and ratings against each vendor’s own site rather than trusting secondhand roundups. I also paid attention to which tools genuinely held up as some of the best software documentation software available, versus ones that just showed up on every comparison list by default.
• Documentation Type Fit: Some tools try to be everything, API reference, product guide, and internal wiki all at once. I checked which ones actually excelled at the specific type they claimed to serve, instead of just covering it adequately. A tool that’s decent at three things usually loses to one that’s genuinely excellent at the one thing you actually need.
• Collaboration Model: A tool that works great for an engineer already comfortable with Git can still be a nightmare for a non-technical contributor. I tested both sides of that equation for every entry on this list, since a documentation tool only works if the people who need to write in it actually can.
• Pricing Transparency: Several of these tools had quietly repriced since older comparison articles were written. I pulled current numbers directly rather than repeat figures that were already stale, since a wrong price is worse than no price when someone’s actually trying to budget.
• AI Capability Depth: “AI-powered” on a pricing page can mean a genuine drafting assistant or a basic keyword search with a chatbot slapped on top. I dug into which one each tool actually delivered, since that label gets stretched pretty thin across a lot of these listings.
• Personal Experience: Beyond reading specs, I spent real time inside each platform, and I weighed that hands-on impression against how people across support, product, and engineering roles actually described using these tools day to day. Where those two things agreed, I trusted it; where they didn’t, I dug further before drawing a conclusion.

What Are My Top 3 Picks for Software Documentation Tools?

Still comparing options? Here’s where I’d send most teams, one pick per lane.

1. ProProfs Knowledge Base

Of all the software documentation tools on this list, ProProfs Knowledge Base is my top pick for teams that need documentation published without a code-based workflow standing in the way. AI Knowledge Brain keeps content accurate as it grows, AI Search Assistant gets readers a direct answer instead of a list of links, and the whole thing runs a public help center, internal wiki, and technical docs from one account. The free plan means you can test all of this before committing to anything.

2. Mintlify

Mintlify is my pick for API-first teams that want documentation to stay in sync with their codebase automatically. I found the Workflows agent drafts documentation updates directly from code changes, and AI traffic analytics show exactly which AI agents are querying the docs and where they’re hitting gaps, a category of visibility most tools on this list don’t offer at all.

3. Docusaurus

Docusaurus is the right call if you’re an open-source project or engineering team that wants complete control over your documentation site and doesn’t mind managing the infrastructure yourself. I found it free, built on React, and it powers documentation for projects like React Native and Redux Toolkit.

Which Type of Software Documentation Tool Does Your Team Actually Need?

Most teams start by asking “which tool is best,” when the more useful question is “which lane are we actually in.” A tool built for one lane rarely does the other two well, no matter how good its marketing sounds.

Tools Built for Accessible, Non-Technical Documentation

These four don’t require Git, Markdown, or YAML to contribute, so anyone on a support or product team can publish without engineering help.

Tools Built for Docs-as-Code, Git-Native Workflows

These four assume contributors are comfortable with Git and version control, and reward that comfort with deep flexibility and zero licensing cost. According to Postman’s 2025 State of the API Report, 93% of API teams face collaboration challenges, with documentation gaps cited by 55% of respondents, the single most common blocker.

Tools Built for API-First Documentation

These four exist specifically to turn an OpenAPI spec into something developers can read and test, not to handle product guides or internal wikis.

If your team spans more than one of these lanes, that’s normal. A support team publishing customer-facing help content and an engineering team maintaining internal API docs aren’t necessarily wrong to use two different tools, they’re just solving two different problems.

What Actually Matters When You’re Comparing These Software Documentation Tools?

Feature lists make every tool sound similar. What actually separates a good fit from a bad one comes down to two questions: which AI capabilities are genuinely worth paying for, and which basic features you shouldn’t compromise on regardless of how good the AI pitch sounds.

AI Features Worth Paying For

Not every AI feature on a pricing page delivers real value, and in documentation tools specifically, a newer category has emerged that most buying guides still ignore: whether your docs are actually readable by AI agents, not just AI-generated.

• Documentation That Stays in Sync With Code: Keeping docs updated is normally a manual task someone has to remember to do. A tool that watches code changes and drafts the update automatically, the way Mintlify’s Workflows agent does, or flags what’s gone stale, the way ProProfs’ AI Knowledge Brain does, closes that gap before a reader ever hits outdated information.
• Search That Understands the Question, Not Just the Keywords: A person typing a question in plain language should get a direct answer, not a list of loosely related articles they have to sort through themselves.
• Visibility Into What AI Agents Are Actually Asking: As more traffic to documentation comes from AI agents rather than people, a growing number of tools expose that traffic directly. GitBook’s MCP server analytics and Mintlify’s AI traffic analytics both show which agents are querying the docs and where they’re hitting gaps, a category of insight that didn’t exist a year ago and is quickly becoming a real differentiator.
• Structured Access for AI Agents, Not Just Search Engines: Several tools on this list, GitBook, Mintlify, Read the Docs, and Redocly’s Enterprise tier, now generate llms.txt files or expose an MCP server so an AI agent can query documentation directly, rather than scraping a rendered page the way a search engine would.

Worth Being Skeptical Of:

• Full AI Autonomy Claims: Any claim that AI fully replaces a person reviewing what gets published before it goes live.
• Vague “AI-Powered” Labels With No Specifics: If a vendor can’t name what the AI actually does, day to day, treat “AI-powered” as a marketing label rather than a real capability.

Core Features You Shouldn’t Compromise On

AI gets the attention, but the basics still decide whether a documentation tool actually gets used six months from now.

• A Collaboration Model That Matches Who’s Actually Writing: If contributors are mostly engineers comfortable with Git, a docs-as-code tool fits naturally. If support staff or product managers need to contribute without learning Git first, a visual editor isn’t optional, it’s the difference between documentation getting written and documentation getting skipped.
• Versioning for More Than One Product Release: A tool that can only show one version of the truth at a time becomes a liability the moment you’re supporting two product versions simultaneously.
• Search That Actually Returns Something Useful: Test this with real questions before signing anything, not the vendor’s demo queries.
• A Genuine Way to Test Before Committing: A free tier or trial that works with your own content, not just a sales demo, is what lets you catch a bad fit before you’ve paid for it.

Pick the Lane First, Then the Tool

I’ve learned the best software documentation tool is the one my team actually kept using. I started with a shortlist of two or three based on which lane I was actually in, developer-first, API-first, or non-technical, and brought in the people who’d be maintaining the documentation day to day, not just whoever was evaluating tools.

In my experience, most tools here solve one lane well: Mintlify and Redocly for API-first teams, Docusaurus and MkDocs for open-source projects that want full control. If you’re only producing one type of documentation, that specialization is exactly what you want.

But most teams don’t stay in one lane for long. I’d point you to ProProfs Knowledge Base for that shift, it covers a public help center, internal wiki, and technical documentation from one account, with AI built into search, writing, and content upkeep from day one. Its forever free plan covers up to 25 pages with every premium feature included, so you can test it with your own content before deciding on anything.