Rezi: From a $9.69 Word Template to $257K MRR in 10 Years — an AI Resume SaaS Whose Slow Start Can Be Verified on Stripe

“AI resume tool” is by now shorthand for an idea anyone can build overnight. Yet one of the largest players in that market is a company that has been solving the same problem since seven years before ChatGPT. Ten years ago, this was a $9.69 Word template. As of August 2026, Rezi, an AI resume builder for job seekers, shows MRR of $257,935, cumulative revenue of $9.9M, and 10,689 active subscriptions — verifiable in real time on a public Stripe-connected dashboard (trustmrr). The small template business founder Jacob Jacquet started in 2015 took ten years to grow to this size.

The problem Rezi solves is concrete. In US hiring, applications are first screened mechanically by applicant tracking systems (ATS). A resume that doesn’t get dropped before a human ever reads it (keywords, formatting, and structure optimized for the ATS) is what the AI generates and edits. Pricing is $29 a month for Pro, or a $149 one-time purchase. It is a business that sells into the time-boxed, urgent problem of a job search.

Jacquet is American, but he moved his base to Seoul, South Korea, and runs the company from there. Serving the enormous demand of the US hiring market without carrying US payroll, separating the market from the base, is also one of the conditions that let a bootstrapped company last ten years.

The timeline in numbers

Starting at $9.69

The first product, in 2015, was a Word template laid out to pass ATS screening. Price: $9.69. Not even software. But this cheap experiment validated that the demand was real, people will pay for “a resume that machines don’t reject”, and laid the groundwork for the later move to SaaS. Buying only the market’s reaction with a minimal product is the standard playbook of validating before writing code, practiced naively in 2015.

It took ten years — and built ten years of moat

Rezi’s growth curve is strikingly slow even among the solo SaaS cases we have recorded. The first five years were template sales and trial and error. Real growth as a SaaS began only after AI was added. The recent trajectory, from ARR $3.2M in 2024 to MRR $257K in 2026 (about $3.1M annualized), also shows that the fast-growth phase is already over and the company has entered the stage of holding steady on a plateau. But that slowness ended up building two moats.

One moat is SEO accumulation. The “resume” keyword family is a huge market whose searchers are replaced every year, and Rezi has ten years of content and domain trust banked. Search is the main route for its roughly 1 million new users a year. For a latecomer to catch up without ad spend would take the same number of years. Making search the main battleground is the same structure as Snappa at $62K MRR, but because Rezi’s market replaces its customers every year, the compounding of that accumulation works even more cleanly.

The other is the timing of AI adoption. Jacquet wired GPT-3 into resume generation in December 2020, two years before ChatGPT’s release. Now that “AI for resumes” has become a commodity anyone can build, Rezi still holds the SEO and the brand as one of the earliest implementers. It is a case where being early got converted into search assets, rather than technical uniqueness.

Subscriptions in a market where the customer disappears in two years

A resume tool’s customer cancels the moment they land a job. To hold $257K in MRR in a market with structurally short LTV, the intake tap must stay open at all times. Rezi’s answer is search, and selling a monthly plan alongside a $149 one-time purchase. The one-time plan catches the “I only want this for the job hunt” demand, and in a market premised on churn, the way of selling that cannot be churned (a one-time purchase) actually reads as honest to customers. Like BoltAI’s perpetual-license strategy, it is billing design fitted to how long the market actually uses the product.

In 2025 it was also reported that Google signed an enterprise contract self-serve, without any sales motion. A company with no sales team has one of the world’s largest enterprises applying on its own, the asset of staying findable in search began to function not just for B2C acquisition but as a B2B entrance too.

The averages are worth a look as well. 10,689 active subscriptions against $257,935 MRR, about $24 per subscription per month. That is a plausible level for a mix of $29 Pro and $149 one-time purchases, and it reveals a distributed revenue structure built from ten thousand small accounts rather than dependence on a few large ones. The decision to pay $24–$149 for the major personal event of a job search is not very cyclical, if anything, demand has the contrarian property of rising in times of employment anxiety.

Risks and limits

Verifiability extends only to the Stripe-connected portion on trustmrr. The account of how the company grew rests on secondary sources, and this article is written along that dividing line. As business risks, three loom largest: (1) AI resumes could lose value through countermeasures on the ATS side (AI-generation detection) or shifts in hiring practice, (2) ChatGPT itself is always right next door as the free alternative, (3) dependence on search-algorithm changes. (2) in particular is the question facing all SaaS in the AI era: can you keep selling, as a dedicated tool, work that a general-purpose AI can do?

What transfers, and what doesn’t

Take away the resume specifics and the pattern still holds: (1) markets whose customers keep turning over (job hunting, exams, moving) are where SEO assets compound best, (2) with a new technology, the very fact of having adopted it first becomes a search and brand asset, (3) in short-LTV markets, selling a one-time purchase alongside subscriptions is rational.

As for limits: the precondition of keeping going for ten years is one most individuals cannot meet. Rezi’s first five years are a stretch that, by this site’s own standards, would have been recorded as “a case that isn’t growing”, and the money and nerve to keep going through slow growth are this case’s invisible precondition. For a slow-compounding cousin, see ProjectionLab’s $1M in 4 years. For a fellow open dashboard, see SEObot.