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 is my dashcam footage useless when I actually need it for a claim?

BlackVue and Viofo owners record terabytes of footage but cannot find the 30 seconds around an incident, and license plates are often unreadable.

Category: Automotive & Mobility · Trend: Vision · Opportunity score: 8.3 / 10

What is the “Why is my dashcam footage useless when I actually need it for a claim?” problem in 2026?

BlackVue and Viofo owners record terabytes of footage but cannot find the 30 seconds around an incident, and license plates are often unreadable.

Who has this problem?

Rideshare driver or daily commuter with a dashcam after a hit-and-run.

Recorded source context

Dataset source note: I have 4TB of footage and my insurance needs the clip from Tuesday around 6pm. I have been scrubbing for two hours and the plate is too blurry to read anyway.

This note may summarize the referenced material rather than quote it verbatim. Source label: r/Dashcam threads on BlackVue and Viofo footage search..

Existing players in this space

BlackVue Cloud: Storage, no search or plate enhancement.
Viofo desktop player: Manual scrub only.

What existing players are missing

Local AI that indexes dashcam footage by event, time, GPS, and detected plates, with super-resolution on the plate region for claims.

How Real Problem AI scores this opportunity

Aggregate score: 8.3 / 10. Four-axis rubric:

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

How to build a solution: stack hints

YOLO for event detection
Real-ESRGAN for plate super-resolution
Whisper for audio events
Electron desktop app