Verbi: AI Oral Practice Breakthrough, $100K Monthly
I recently came across the story of indie developer Pedro Machado, which is pretty interesting. He built an app called Verbi for AI-powered speaking practice, and in the first month alone, he made $102K—bringing his cumulative revenue to $186K, up 187% month over month.
Honestly, language learning is already a bloodbath. Duolingo and other giants own most of the market. But instead of competing head-on on general interest, Pedro targeted a real pain point: years of English study, yet too scared to speak and lacking real-world context.
Why did this niche work?
Traditional flashcards only solve “word recognition,” not “speaking.” Verbi makes “talking” its core deliverable, so users are willing to pay a premium for instant, AI-driven conversation feedback. And for an indie dev, this is a classic tool play, not a content play—no team overhead, near-zero marginal cost, and growth driven by product-led ASO rather than paid ads.
Here’s how you’d cold-start if you wanted to copy this path:
- Step 1: Make a single-point entry. Don’t try to build an all-in-one language school. Pick one specific scenario, like “IELTS speaking mock” or “business meeting English.”
- Step 2: Build an ultra-minimal MVP. Ship a voice-interaction demo that highlights the value of a “3-minute AI speaking session.”
- Step 3: Validate cheaply. Launch on Product Hunt, Xiaohongshu, or TikTok. Your main costs will be a few hundred bucks for APIs and server hosting.
If day-1 or day-7 retention exceeds 20%, then consider investing more in ASO and optimization. Keep the whole cycle to 2–4 weeks, and the risk stays low.
But there are traps to avoid, too.
The biggest risk is being crushed by big tech. If Duolingo or ChatGPT ships similar features quickly, smaller players get squeezed out. The counterplay is to go deeper into vertical niches—lesser-known languages or industry-specific speaking skills—building proprietary corpora and prompt-engineering moats, and delivering the fine-tuned experience big players won’t bother with. Also, watch compliance: enforce strict content filters to sidestep privacy issues.
All in all, this case proves that high-level speaking practice carries serious pricing power. If you have enough technical chops, do some homework on competitor pricing and traffic patterns in the Apple ecosystem—you might just find your own wedge.
Source · TrustMRR · Verified Revenue: Read original →