NotFair: AI-agent ads and workflows, $11K MRR: approval previews

NotFair lets operators manage advertising and website workflows through AI agents. Its $11K MRR is verified through the payment provider's API by TrustMRR (Stripe), as of September 30, 2026.

What it actually sells

NotFair is a hosted integration platform for people who want to work with their business tools through an AI agent. It connects advertising, search, analytics, CRM, and website workflows.

The site says, “For operators making real campaign changes.” Its features include diagnosing account issues, drafting campaign changes, and previewing bid, budget, keyword, audience, and ad edits before approval.

How it charges

The product's price could not be identified on the pages we read. Currency amounts appear on the pages, but none could be tied to the product's own pricing. NotFair is sold as a hosted integration platform for business tools used through an AI agent.

Month by month

Monthly revenue as read from the payment provider by TrustMRR, in US dollars, as of September 30, 2026.

Month	Revenue (USD)
2026-04	$248
2026-05	$5,285
2026-06	$6,819
2026-07	$7,136
2026-08	$15,134
2026-09	$14,311

Where customers come from

NotFair works with Claude, ChatGPT, Codex, Cursor, OpenClaw, and Hermes. WordPress access requires a verified website and the NotFair plugin with MCP enabled.

What stands out

NotFair previews proposed edits, provides full change history and one-call undo, and supports bulk workflows for keywords, ads, budgets, and scripts. It manages ads across Google, Meta, X, LinkedIn, Reddit, and TikTok.

One customer reports that monthly leads increased from 111 to 315 and that cost per lead fell from $106 to $43. A clinic owner reports that incoming leads doubled after 60 days and approached triple in month three.

Two named customers gave NotFair five stars on Trustpilot in September 2026: a clinic owner taking its ads in-house and an agency that runs ads for clients.

From the official site

For operators making real campaign changes.

Diagnose account issues and draft campaign changes

Excerpts from the official website, fetched October 1, 2026.

Where it sits in the data

NotFair's $11K MRR is higher than 94% of the 5,602 projects with payment-verified revenue in our dataset; the median across them is $150. Within the “Analytics” category (646 projects) it is higher than 94% (category median $135). Snapshot: 2026-09-02 to 2026-09-30. The dataset only covers founders who chose to publish their numbers, so it leans toward businesses that work; use it for scale, not as an average.

Currency

All figures are in US dollars as published. A rough yuan or euro conversion is not applied here because prices, taxes and acquisition costs differ by country.

Could you build something like this?

My view is that this needs real work. The buyer is an operator managing advertising, search, analytics, CRM, or website workflows through an AI agent. Distribution would depend on compatibility with agent clients and the connected business platforms.

The difficult parts are maintaining reliable connections, handling permissions and approval flows, supporting campaign changes, and managing competition. Operators may also need controls around account access and edits. Those requirements make the product harder than a basic AI-agent interface.

Verdict: Hard to replicate.

One thing to take from it

The clearest product hook is the approval flow: proposed bid, budget, keyword, audience, and ad edits appear before approval, with full change history and one-call undo.

Sources

NotFair official website, fetched October 1, 2026
NotFair pricing page, fetched October 1, 2026
NotFair about page, fetched October 1, 2026
TrustMRR: revenue verified through the payment provider's API by TrustMRR (Stripe), as of September 30, 2026

Revenue, team and start-cost figures are what the founder reported at the interview date, not current figures and not a prediction of what you will earn. Product and pricing facts come from the business's own website as checked on 30 September 2026. Method & sources · Disclosure