I kept needing the same thing while writing AI tool comparisons: a clean, current list of what these tools actually cost. Not a screenshot from a pricing page that changed last week. Not a "starts at $$$" marketing line. Real, structured numbers I could sort, chart, and reason about.
So I built one, and now I've published it as open data.
What it is
A single JSON file with every AI and productivity tool I've reviewed hands-on, one record each:
{
"name": "Claude",
"category": "AI Assistants",
"free_tier": "Yes",
"entry_price_display": "$20/mo",
"entry_price_usd_monthly": 20,
"best_for": "Long-form writing, analysis, and coding",
"review_url": "https://aitoolsinsiderhq.com/articles/claude-ai-review-2026.html",
"editor_pick": true
}
31 tools across 11 categories (AI assistants, writing, SEO, design, email, CRM, productivity, project management, video/audio, automation, and one piece of hardware). It ships with a summary block too, so you don't have to compute the obvious aggregates yourself:
"summary": {
"tools_total": 31,
"software_tools": 30,
"average_entry_price_usd_monthly": 24.66,
"median_entry_price_usd_monthly": 15.5,
"with_free_tier": 28,
"with_free_tier_pct": 93
}
Grab it here: https://aitoolsinsiderhq.com/ai-tools-dataset.json
Why JSON and not another blog table
Because data you can fetch() is data you can actually use. A few things I do with it:
Compute the spread in three lines of Python:
import urllib.request, json
d = json.load(urllib.request.urlopen("https://aitoolsinsiderhq.com/ai-tools-dataset.json"))
paid = [t["entry_price_usd_monthly"] for t in d["tools"] if t["free_tier"] != "N/A"]
print(f"avg ${sum(paid)/len(paid):.2f} cheapest ${min(paid)} priciest ${max(paid)}")
Or pull it straight into a frontend:
const res = await fetch("https://aitoolsinsiderhq.com/ai-tools-dataset.json");
const { tools } = await res.json();
const seo = tools.filter(t => t.category === "SEO").sort(
(a, b) => a.entry_price_usd_monthly - b.entry_price_usd_monthly
);
The interesting findings fall out fast: the median entry plan is $15.50/mo but the mean is $24.66 because a handful of SEO suites drag the average up; 93% of these tools have some free tier; project management is the cheapest category and SEO is the most expensive. None of that is surprising in isolation, but having it as queryable data makes it easy to fact-check a claim or build something on top.
Don't want to parse it? Embed the live table
If you're writing a post and just want a maintained comparison table that updates when prices change, the rendered version is embeddable in one line:
<iframe src="https://aitoolsinsiderhq.com/ai-tools-database.html?embed=1"
width="100%" height="720" loading="lazy" style="border:0"
title="AI tools comparison"></iframe>
It strips the site chrome and shows a sortable, filterable table with a small "powered by" link back. I'd rather you drop that in than copy a static table that's wrong in a month.
The honest caveats
- Prices are the published entry-level paid plan for 2026 (annual billing where that's the headline), pulled from my reviews. They're a starting reference, not a live quote. Vendors change plans; confirm on the tool's own site before quoting a number in something important.
- It covers tools I've actually used and written up, so it's opinionated by construction, not an exhaustive market scrape.
editor_pickis just that: my pick, flagged honestly so you can ignore it. - One hardware item has
free_tier: "N/A"and is excluded from the price aggregates.
License
CC BY 4.0. Use any of it, in a post, a chart, a side project, a model eval set, whatever. Just attribute it with a link back to https://aitoolsinsiderhq.com/. That's the whole deal.
I regenerate the file from the same source the comparison site is built from, so it can't silently drift from the pages. If a price looks off, tell me and I'll fix it at the source. And if you build something fun with it, I'd genuinely like to see it.
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