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 Class 12 board prep cost ₹50,000 and still mean PDFs and photocopies?

Indian Class 12 students pay ₹40k-₹2L/year for board + JEE/NEET coaching that runs on photocopied notes and shared PDFs; AI tutoring options are fragmented or English-first.

Category: EdTech · Trend: LLM · Opportunity score: 8.4 / 10

What is the “Why does Class 12 board prep cost ₹50,000 and still mean PDFs and photocopies?” problem in 2026?

Indian Class 12 students pay ₹40k-₹2L/year for board + JEE/NEET coaching that runs on photocopied notes and shared PDFs; AI tutoring options are fragmented or English-first.

Who has this problem?

Class 11 and 12 students in India preparing for board + JEE/NEET, and their parents paying for coaching.

Recorded source context

Dataset source note: Spent ₹65k on coaching. Half the value was photocopies of last year's papers.

This note may summarize the referenced material rather than quote it verbatim. Source label: BYJU's, Unacademy, Vedantu user threads + Telegram coaching groups.

Existing players in this space

Physics Wallah: Mass content; not personalised tutoring.
BYJU's / Vedantu: Recorded lectures; weak adaptive layer.
Khan Academy: English; mismatched with NCERT.

What existing players are missing

An NCERT-aligned, Hindi+English AI tutor that knows what the kid got wrong yesterday and drills exactly that today; sells direct to parents at ₹1,499/mo undercutting coaching.

How Real Problem AI scores this opportunity

Aggregate score: 8.4 / 10. Four-axis rubric:

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

How to build a solution: stack hints

NCERT corpus + past-paper bank
Adaptive learning engine
Voice tutor in Hindi/English
Parent dashboard