AI Boxs · About us
Explore AI tools with more clarity.
AI Boxs helps people discover AI software, understand product trade-offs, and make better-informed decisions through organized tool listings, research-led articles, comparisons, and clearly identified hands-on reviews.
Discover. Understand. Evaluate.
Different content serves different needs. We aim to make the distinction visible before you rely on an article.
Make a crowded AI market easier to navigate.
Our goal is to help readers ask better questions before choosing a tool—not to suggest that one product is right for everyone.
Our purpose
Useful information, without confusing discovery with proof.
AI software changes quickly. Features, pricing, usage limits, availability and data policies can shift, while marketing pages often focus on best-case outcomes. Comparing tools can take time, especially when products solve similar tasks in different ways.
AI Boxs organizes tools by category and publishes articles that explain capabilities, practical use cases and limitations. We aim to show readers what is documented, what has been researched, and what has actually been tested—so those distinctions are easier to judge.
What we publish
Three types of content. Three different purposes.
A tool appearing in our directory does not automatically mean it has been tested or scored. Look at the format and evidence shown in each article.
AI Tools Directory
Browse products by task or category and follow links to the providers for the latest details.
- Organized product listings and category pages
- Useful as a starting point for discovery
- Not a scored ranking or proof of hands-on testing
Research & Comparisons
Articles that analyze documented information to explain differences, costs, product fit and trade-offs.
- May use official documentation, pricing and release notes
- Separates source-based facts from editorial analysis
- Does not imply personal testing unless stated
Hands-on Reviews
Reviews that present direct testing should explain the scope and conditions behind the findings.
- Test scope, plan or version where available
- Observed strengths, limitations and failure cases
- Scores only where a stated framework is applied
Our editorial approach
How we work
The exact process depends on the format of the article. These principles help readers understand the basis and limits of what we publish.
Define the question
Identify the task, likely audience, and decision the article is intended to support.
Check available sources
Use product documentation, pricing pages, release notes and other relevant information where available.
Show the evidence
For hands-on reviews, explain what was actually tried. For research articles, distinguish documented facts from analysis.
Update or correct
Revise information when material changes are identified and consider reader reports about errors or outdated details.
Who writes at AI Boxs
A named editor, with clear responsibility.
We identify the person responsible for editorial decisions rather than presenting an unnamed team.
YAN
Editor & Lead ResearcherAI Boxs is currently written and edited by YAN. Coverage focuses on AI tool discovery, product research, comparisons, pricing considerations and workflow fit.
Editorial work includes deciding which questions to cover, organizing available evidence, explaining practical trade-offs and identifying when information needs further verification. Where a piece presents hands-on testing, its content should state what was tested and what the findings can—and cannot—show.
Our principles
What readers should be able to expect.
Clarity about evidence
We aim to distinguish information from product providers, our own analysis, and observations from hands-on tests.
Balanced trade-offs
Useful coverage includes limitations, access requirements, pricing considerations and situations where another option may fit better.
Corrections matter
Product details can change. Readers can contact us to flag inaccuracies or pages that may need updating.
Editorial standards
Methodology & editorial policy
Our methodology explains the scoring framework used for relevant reviews. The editorial policy describes how content is handled and how facts, analysis and testing should be distinguished.
Commercial transparency
Affiliate disclosure
Some links on AI Boxs may earn a commission if you make a purchase, at no additional cost to you. Affiliate relationships should be disclosed and should not be treated as evidence that a product is the best choice.
Quick answers
About AI Boxs: common questions
Are all tools in the directory tested?
No. The directory is a discovery catalog, and most listings have not been hands-on tested by AI Boxs. Look for a separate review with a stated test scope.
Where does product information come from?
Research articles may draw on official product pages, documentation, pricing pages, release notes and other relevant sources. The source base depends on the topic.
Do you score every AI product?
No. A score should appear only when an article applies a stated scoring framework and provides enough context to understand the result.
How can I report an error?
Use the contact page to send a correction or flag information that may be out of date.
Start with the task you need to solve.
Browse the directory to discover available tools, or read our research and reviews to understand the options in more depth.