$0 to first paying customer: building GenCrafters in 2026
The AI tool fragmentation problem is real – here's how I'm solving it
Quick poll before I get into it: how many AI image/video platform subscriptions are you currently paying for?
I'm guessing for most people here it's at least 2–3. For me it was 4, and I was still missing access to models I wanted to use.
The problem isn't that any single tool is bad. Midjourney is great at what it does. So is Runway. So is Sora. The problem is that the best model for any given task changes depending on the task — and right now, each of those models demands its own account, subscription, and learning curve.
This is the problem I've been working on.
GenCrafters (https://gencrafters.com) is a platform that aggregates 20+ AI image and video models under one interface and one credit balance. You don't need separate accounts. You don't need to manage separate billing. You pick the model, write your prompt, and generate.
Currently supported:
- Images: Flux 2 Pro, DALL-E 3, GPT Image 2, Grok, Nano Banana (Google), Qwen (Alibaba), Seedream (ByteDance), Wan
- Video: Sora 2, Kling 3.0, Veo 3.1, Seedance 2
Credit-based pricing — packs from $4.99, no expiry, no forced subscription. Free credits on signup.
I'd genuinely love to hear how others here are handling this. Are you a one-tool person? Do you switch? Have you found something that solves this already?
The interesting part here may not be the models.
Most creators already know there are dozens of image and video models.
The harder problem is deciding which one to use without wasting credits, time, and trial-and-error.
I'd be careful not to position GenCrafters as "20+ models in one place," because that can accidentally make the buyer think they now have 20 decisions instead of one.
The stronger story may be around reducing AI-tool fragmentation and decision fatigue.
Happy to put the tighter positioning angle in writing if useful. I think there's a real difference between being a model directory and being the default place people go when they just want the best output without thinking about the model first.