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.

My chatbot promised a refund policy that does not exist and now we owe the customer.

Courts increasingly hold companies to what their AI assistant says, and nobody is checking the bot against the real policy.

Category: LegalTech & Compliance · Trend: LLM · Opportunity score: 9.0 / 10

What is the “My chatbot promised a refund policy that does not exist and now we owe the customer.” problem in 2026?

Courts increasingly hold companies to what their AI assistant says, and nobody is checking the bot against the real policy.

Who has this problem?

Support and legal leads at any company running a customer-facing LLM.

Evidence this problem is real

“The assistant invented a policy, the tribunal said the company owns what the bot says, and we paid.”

Sourced from Chatbot-liability rulings and reporting, 2026. (link)

Existing players in this space

Guardrails / NeMo: Block unsafe text, not policy contradiction.
Prompt instructions: Ignored under pressure, no proof trail.
Human review: Cannot scale to every live conversation.

What existing players are missing

A real-time claims-check that verifies every promise a support bot makes against the company's actual policy set and logs a defensible record before the message sends.

How Real Problem AI scores this opportunity

Aggregate score: 9.0 / 10. Four-axis rubric:

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

How to build a solution: stack hints

Policy knowledge base + retrieval
Claim-extraction + contradiction check
Pre-send gate
Immutable audit log