How We Review AI Tools

Tools reach this site two ways: our editors research them, or their makers launch them here. Both go through the same review before anything is published.

That review confirms the product is live and reachable, that its description matches what the tool actually does, and that its pricing model, category and key features are recorded accurately. Tools that fail the check are not approved. We read the tool’s own pricing, docs and policies, check its claims against independent sources, then give it one Editor Score out of 5 from one published method. Reviews are re-checked on a rolling basis, and every review shows when it was added and when it was last updated.

Our reviews are research-based. When a review includes hands-on testing, its method note says so. Scores are never for sale, and paid placements are always labelled.

How to Choose the Right AI Tool

The right tool depends on the job, not on how well known it is. Six things worth checking before you commit:

1. Start with the task. Name the specific job — drafting posts, removing backgrounds, summarising research — then open the category that covers it.
2. Compare capabilities, not claims. Most tools in a category describe themselves the same way. Compare what they actually produce.
3. Check the pricing model and its limits. A free tier usually carries a usage cap. Work out whether that cap fits how often you will really use it.
4. Check it fits your workflow. A tool you have to leave your existing setup to use tends to get abandoned.
5. Read the limitations. Knowing where a tool stops is more useful than another list of what it does.
6. Try before you commit. Run a real task of your own through it, not the vendor’s demo.