What is Real Problem AI?

Real Problem AI is a curated directory of 200+ 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 200+ 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 reconciling Stripe payouts to my bank still take a full day each month?

Small SaaS and D2C founders spend a day a month matching Stripe (or Paddle, Shopify Payments) payouts to bank deposits, untangling fees, refunds, chargebacks and currency conversion by hand.

Category: FinTech · Trend: Agents · Opportunity score: 7.5 / 10

What is the “Why does reconciling Stripe payouts to my bank still take a full day each month?” problem in 2026?

Small SaaS and D2C founders spend a day a month matching Stripe (or Paddle, Shopify Payments) payouts to bank deposits, untangling fees, refunds, chargebacks and currency conversion by hand.

Who has this problem?

Solo and small-team founders doing their own bookkeeping on Stripe/Paddle/Shopify.

Evidence this problem is real

“Stripe pays out a lump sum. My bank shows a different number after fees and FX. Matching the two, with refunds and chargebacks mixed in, is a full Saturday every single month.”

Sourced from Indie Hackers and r/SaaS 2026 bookkeeping threads, Stripe payout-reconciliation support discussions, fractional-CFO posts.

Existing players in this space

QuickBooks / Xero — Imports data, reconciliation still manual
A2X — Good for Amazon/Shopify, narrow
Stripe reporting — Raw data, no bank match

What existing players are missing

A reconciliation agent that maps each Stripe payout to the exact bank deposit, splits out fees, refunds, chargebacks and FX automatically, and posts clean journal entries to QuickBooks or Xero. The monthly day becomes a 5-minute review.

How Real Problem AI scores this opportunity

Aggregate score: 7.5 / 10. Four-axis rubric:

Problem severity: 7 / 10
AI feasibility today: 9 / 10
Market signal: 8 / 10
Competition gap: 6 / 10

How to build a solution: stack hints

Stripe/Paddle/Shopify payout ingestion
Bank-feed matching (Plaid)
Fee/refund/FX decomposition
QuickBooks/Xero journal posting