A credit-based AI video generator sold to content creators — $100,000 in its first year at 60% margin, with zero ad spend, distributed by shipping its own API inside free n8n automation templates
roughly $15,000/mo and rising · ~60% profit margin · zero advertising budget · revenue is mostly credit consumption rather than subscriptions, so the founder tracks videos generated per customer instead of MRR · 60+ video effects and prompts in the library · prior company (3D-model and AI-image dashboard) sold to a much larger company after roughly €150,000 of software spend over 18 months
Fewer bars = easier, cheaper, or faster for an AI-assisted solo builder. Editorial judgments based on the case details.
Four years before this video, the founder started his first SaaS. It began as an agency: he built 3D models for companies — starting deliberately with carpet retailers, because carpets are easy to model and he could close them fast — and gave each client a simple branded panel with their own login to review and track their models. "We were working in agency logic. We weren't SaaS. That was just their interface." Clients loved it. He used the agency revenue to develop the product further, then added AI image generation on top when that was still novel and remarkable. "At the time this was incredibly new. It was very popular, and we made the first AI images of that type — nothing comparable to today's quality, but for that time it was something very, very valuable." That is the point at which it became a real self-serve product: users signed up, took subscriptions, bought credits and used the system themselves. He puts the software spend at roughly €150,000 over 18 months, in the pre-Claude-Code era where every line had to be written by hand. That company was sold to a much larger one. The second venture, the subject of this breakdown, targets AI content creators. The insight came from watching them struggle: they wanted to do YouTube automation but could not work out what prompts to write, how to make long videos, or how to construct a scenario. So he built a ready-made template library plus a system that could assemble 8-to-10-minute videos. Within one year it has done $100,000 in sales — around $15,000 a month and, he says, continuously increasing. He also mentions two other ventures, Left Flow and Core Magnet, plus an agency model, which he deliberately excludes from the numbers here.
6 more sections — the full story, the playbook, the risks, and the numbers. Free account unlocks everything.
Create free accountEmail code only. No password.The quick-reference card — acquisition channels, replication playbook, and risk map — unlocks with a free account.
Create free accountEmail code only. No password.Paste into Claude Code / Codex and get a working version of this product end-to-end.
Two production-grade prompts per idea: a full build spec and an SEO growth plan. Copy, paste, ship.
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Create free accountEmail code only. No password.Data credibility: Founder-reported in a Turkish-language presentation-to-camera. No dashboard, Stripe screenshot or third-party verification of the founder's own figures appears at any point, which matters because his stated principle is the opposite: he argues at length that people claiming millions should instead post revenue on a Stripe-connected marketplace where the number cannot be edited, and cites examples from that marketplace (an app with $270,000 in cumulative earnings and $36,000 monthly revenue asking nearly $2 million; a 'Brainroad'-style company at $33,000 MRR). He applies that standard to others while reporting his own numbers verbally. Self-reported figures for the current product: $100,000 in sales in its first year, roughly $15,000 a month and rising, about 60% profit margin, credits priced at 1.5-2x a roughly $1 model cost, 60+ effects and prompts in the library, and zero ad spend. For the previous company: roughly €150,000 of software development spend over 18 months, and a sale to a much larger company with no price disclosed. He also names Left Flow and Core Magnet as other ventures and an agency model, all deliberately excluded from these numbers. Cold-email metrics (7-15% reply rate on the permission-asking opener; 1.5% → 4.5% → 6-7% across three emails) are his own reported figures. IMPORTANT NAMING CAVEAT: the auto-captions render the product's name inconsistently as Protospal, Protipal, Protpal, Profal, 'Prot B' and 'protez ball', and the first company as ARSPAR, Artsp, Ars and RSper. We have used the most frequent rendering in the name field and flag that neither spelling can be confirmed from the transcript. The Stripe-verified marketplace he refers to is rendered as 'Truster' / 'Trusterarı' and we could not identify it; he separately and clearly names Trustpilot for reviews, so it is a different service. Region is Turkey: the presentation is in Turkish, he calls himself one of the biggest automation names in Turkey, advises viewers to localise US products for Turkey, prices in euros for his old software spend, and names iyzico and PayTR as the local payment processors. The video also functions as promotion for his own paid community and programme, which is a direct commercial interest in these figures.