About 99coupons.ai

A small team trying to fix one annoying corner of the internet.

Coupons. The category was poisoned by SEO farms publishing fifty codes per store, four of which work. We're trying to make this one corner of the web trustworthy again — using a thin team, a careful pipeline, and a lot of AI.

Founded 2026 6 people Remote · US-hosted Independent · self-funded
Our mission

Every coupon code on this site actually works.

Not most of them. Not the popular ones. Every one. If a code is on this site, it was tested at checkout in the last 24 hours. If it doesn't work, we'd rather not show it.

That sounds like a small mission. In a category where 90% of listed codes are dead, it isn't.

"We took the category seriously enough to build the system above."

— pinned to the wall in our editor's room

Origin

How we got here.

01

The pattern was obvious.

Every time we needed a coupon for something, we'd open three sites, click through six pop-ups, reveal twelve codes, and find one that worked. The category had completely abandoned the user.

02

The fix was technical.

Codes fail because nobody tests them. We figured: if you actually test every code at checkout — with an automated cart simulator, AI cross-checks, and a human editor for the edge cases — the category becomes useful again.

03

So we built it.

The pipeline runs every 24 hours across 4,712 stores. Codes that fail twice disappear. The full methodology is documented on /how-we-verify — including the agents we use, the models, and a live verification log.

What we believe

Four principles. They show up in every decision we make.

01.

Don't show what doesn't work.

It sounds obvious. It's almost universally ignored. Codes that fail twice are removed the same day — no sad-face emoji, no "expired" tag at the bottom of the page. They just leave.

02.

Show your work.

Every code has a structured verification log. Anyone can see when it was tested, by which agent, with what result. The methodology is documented in public — not behind a sales page.

03.

Earn the click, don't fake it.

No "Reveal!" buttons on dead codes. No fake countdown timers. The discount shown is the discount the merchant actually applied at checkout — not the one they advertised in a banner.

04.

Small is fine.

6 people. One Hetzner box. A SQLite database that fits on a phone. We didn't raise money. We don't need scale to be good — we need taste and a stubborn verification pipeline.

How we automate

AI does the volume. Humans do the judgment.

We use AI for what AI is good at: scanning thousands of merchant pages for new codes, cross-checking each one against published terms, drafting clean descriptions and FAQs. The humans on the team handle what AI is still bad at — taste, editorial standards, edge cases, and deciding what an "Editor's Pick" is.

The interesting engineering bit is the orchestration: routing each task to the right agent (or the right human) at the right point in the pipeline. That's documented in depth here:

Read the methodology
The team

6 people behind every code on this site.

We're distributed across four time zones. The server lives in Ashburn, Virginia. We meet on Mondays.

M

Mia Chen

Editorial Lead

Former pricing editor at a deal site you've heard of. Sets the bar on what counts as a working code.

R

Ravi Sharma

AI Systems

Builds the verification agents, orchestrator, and the cross-check pipeline.

A

Anna Bergmann

Operations

Keeps the cron healthy, the DB backed up, and the cart simulators behaving.

T

Tomas Lindqvist

Cart Simulator Lead

Reverse-engineers checkout flows the moment they break and writes the resilient ones.

J

Jules Okafor

Editor

Reviews flagged codes, writes the edge-case notes, owns the style guide.

S

Sam Patel

Engineering

Server, scheduler, observability. Wrote most of the structured-log layer.

Get in touch

Found a broken code? Have a tip? Want to work with us?

We read every email. The editorial team responds within a day to anything about a specific code; the rest of the team takes a little longer.