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 shopping for a mortgage refi still feel like 2003?

Loan shopping requires uploading the same docs to 5 lenders, getting hard-pulled, and negotiating opaquely.

Category: FinTech · Trend: Agents · Opportunity score: 7.6 / 10

What is the “Why does shopping for a mortgage refi still feel like 2003?” problem in 2026?

Loan shopping requires uploading the same docs to 5 lenders, getting hard-pulled, and negotiating opaquely.

Who has this problem?

Homeowners refinancing, first-time homebuyers, auto-loan shoppers.

Evidence this problem is real

“I've uploaded my W-2 and bank statements 7 times this week. Each lender has a different portal.”

Sourced from r/personalfinance, r/RealEstate, r/FirstTimeHomeBuyer.

Existing players in this space

LendingTree
Credible
Better.com
Owning

What existing players are missing

A real comparison agent that submits to multiple lenders with one doc vault, manages soft-pull rates, and uses competing offers as negotiation leverage. LendingTree just resells your lead.

How Real Problem AI scores this opportunity

Aggregate score: 7.6 / 10. Four-axis rubric:

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

How to build a solution: stack hints

Encrypted document vault (income, assets, ID)
Lender portal automation via browser agents
Soft-pull aggregator (Experian/Equifax APIs)
LLM negotiation script generator with rate-lock tracker

Why this problem is archived

Crowded category, LendingTree/Better/Owning cover the comparison wedge in 2026.