What is Real Problem AI?

Real Problem AI is a curated directory of 100 real problems worth building an AI startup around. Each problem is scored honestly on severity, AI feasibility, market signal, and competition gap. We're for builders looking for what to build, not for ethics debates about AI.

What is the difference between Real Problem AI and AI ethics or AI risks indexes?

Real Problem AI catalogues problems AI can solve: productive, commercial opportunities for builders. AI ethics indexes catalogue problems with AI itself (bias, environmental cost, copyright, consciousness). Different intent, different audience: founders and indie hackers vs researchers and policy folks.

What should I build with AI in 2026?

Look for problems with high severity (it costs people hours, sleep, or revenue every week), high AI feasibility (LLMs, vision or voice are great at this today), strong market signal (Reddit threads + willingness to pay), and a clear competition gap (incumbents miss the same obvious thing). Real Problem AI scores 100 such problems for you on those four axes.

Where do Real Problem AI's startup ideas come from?

From three sources, scanned each cycle: 1) Reddit threads where people describe a real friction in their own words, 2) podcasts and talks of founders young builders trust (Nikhil Kamath, Aman Gupta, Ankur Warikoo, Raj Shamani, Andrej Karpathy, Greg Isenberg), and 3) a continuous 1,000+ source scan covering forums, app store reviews, regulator filings, and field interviews.

Is Real Problem AI free?

Yes. Browsing every problem, opening every score breakdown, raising your hand on a co-founder match, and the founder vault are all free. There is no paywall.

How is each problem scored?

Four axes, each 1-10, weighted: Problem Severity (30%), AI Feasibility (25%), Market Signal (25%), Competition Gap (20%). Weighted average is the Opportunity Score on each card. Only problems clearing 7.0+ make the live list.

Why does going viral get a small shop's payouts frozen with no reason given?

A two-year-old fashion brand went viral, took about $100k in sales, and four days later every payout was frozen with support unable to say why or for how long, while other merchants report holds of $31k to $500k after verification loops.

Category: FinTech · Trend: Agents · Opportunity score: 8.1 / 10

What is the “Why does going viral get a small shop's payouts frozen with no reason given?” problem in 2026?

Who has this problem?

Small online brands and Shopify or Stripe merchants whose sales spike suddenly.

Recorded source context

Dataset source note: 4 days later, our account payout is frozen by Stripe. All payout blocked. No notice. Nothing.

This note may summarize the referenced material rather than quote it verbatim. Source label: HN post on Stripe withholding a $100,000 balance after a viral sales spike, 19 September 2026, 11 points and 17 comments, with similar Shopify Community threads on $500k and $31k holds the same week. (primary source).

Existing players in this space

Stripe and Shopify Payments risk review: Decide the hold, and rarely explain which signal triggered it or what evidence clears it.
Secondary payment processors: A useful backup, set up only after the damage is done.
Chargeflow: Automates chargeback disputes, not reserve or payout hold appeals.

What existing players are missing

A merchant-side monitor that predicts when a sales spike will trip a processor's risk review, assembles the evidence pack in advance (fulfilment proof, tracking, supplier invoices, refund rate), and drafts a precise appeal the moment a hold appears.

How Real Problem AI scores this opportunity

Aggregate score: 8.1 / 10. Four-axis rubric:

Problem severity: 9 / 10
AI feasibility today: 8 / 10
Market signal: 8 / 10
Competition gap: 7 / 10

How to build a solution: stack hints

Payments and order API integrations
Anomaly detection on sales velocity
LLM evidence pack and appeal drafting
Document store for fulfilment proof