Carver — turn real Hong Kong pain points into a business you can build
Most founders stall on the same question: what should I build? So they copy an overseas app that doesn't fit the local market, or brainstorm ideas nobody actually wants — and quietly give up a few months later.
I built Carver (https://carverhk.com/en) around a different starting point: evidence.
Every day, Hong Kong people describe their real frustrations in public online discussion — the same complaints, over and over. That repetition is the clearest demand signal there is. Carver collects those recurring pain points, hand-curates them weekly, and scores each one on severity, market gap, and willingness-to-pay.
But the part I'm most proud of is what comes next. For any pain point, Carver generates a complete AI business plan:
- a concrete MVP spec
- a six-month cash-flow estimate
- low-cost acquisition channels
- a step-by-step launch sequence
So instead of stopping at "here's an idea," you get "here's exactly how to build it this month."
Why this is hard to copy: anyone can bolt an LLM onto an idea list. The moat is the curated, quantified dataset of real Hong Kong demand feeding it — built specifically for the local market, in Traditional Chinese.
It's freemium: browse curated pain points and full analysis samples free; Pro (HKD 168/mo, ~US$21) unlocks the full library and unlimited AI plans.
Would genuinely love feedback from other founders — especially on the plan-generation output. What would make it something
you'd actually act on?
I like that you're starting with observed demand instead of generated ideas.
The harder challenge isn't whether the pain points are real—it's whether the same evidence can reliably predict businesses people will actually pay for. If you can close that gap, the dataset becomes much more valuable than the AI-generated plans themselves.
This is exactly the right challenge, and honestly the thing we think about most!
You're right that "the pain is real" and "people will pay to fix it" are two different bars. Observed demand gets us past the first one, but not automatically the second.
The way we're trying to close that gap is by weighting signals that hint at willingness to pay, not just volume of complaints: people already paying for a bad workaround, spending real money around the problem, or venting about wasted time and cost rather than mild annoyance.
Frustration attached to money moving is very different from frustration on its own. And you've put your finger on where the real long term value sits.
The AI plans are the useful front end today, but the dataset of validated, willingness to pay weighted demand is the compounding asset. That's the direction we're building toward.
Really appreciate you articulating this!
Glad it resonated.
Your reply made me think there's one strategic decision sitting underneath that compounding dataset which becomes much more significant as the business grows, but I don't think I can explain the reasoning properly in a thread without oversimplifying it.
If you're interested, what's the best email to reach you on?
Appreciate that!
hello@carver.c
om
Hey — quick note.
I just tried sending an email to hello@carver.com, but it bounced back saying the address doesn’t exist or can’t receive mail (“Address not found”).
Thought I should let you know in case there’s an alternative email you want me to use.
sorry , typo
hello@carverhk.c
om
Thanks! I’ve just sent it over.
Looking forward to hearing your thoughts whenever you have a chance.