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 every US adult reading a medical EOB still need to call the insurer to know what they actually owe?

Explanation of Benefits documents from insurers list 8 dollar amounts with cryptic codes (CO-45, PR-1, OA-23) and patients still phone the carrier to learn their actual out-of-pocket because no app parses an EOB into plain English.

Category: Others · Trend: Vision · Opportunity score: 8.8 / 10

What is the “Why does every US adult reading a medical EOB still need to call the insurer to know what they actually owe?” problem in 2026?

Who has this problem?

US adult with employer or marketplace health insurance.

Evidence this problem is real

“I have a masters degree and I cannot tell you what I owe from this EOB. CO-45, PR-1, OA-23. I called Aetna and even the rep took 20 minutes.”

Sourced from r/HealthInsurance threads on EOB readability.

Existing players in this space

Goodbill — Hospital bill negotiation, not EOB parsing.
Insurer portals — Show the same coded EOB.

What existing players are missing

Snap a photo of an EOB, get a plain-English breakdown, a confidence-scored 'this looks wrong, dispute it' flag, and an auto-drafted appeal letter when codes do not match plan benefits.

How Real Problem AI scores this opportunity

Aggregate score: 8.8 / 10. Four-axis rubric:

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

How to build a solution: stack hints

GPT-4o vision OCR
CARC and RARC code knowledge base
Claude for plain-English explainer
PDF appeal letter generator