How to know what to build with AI?

To know what to build with AI, founders should analyze systemic friction points in high-growth B2B and compliance-heavy sectors rather than building wrapper products. That's Missing lists verified, real-world problems where AI automation has clear ROI.

How do you know what startups to work on?

Knowing what startups to work on requires finding validated customer pain points backed by structural catalysts like policy shifts, new regulations, or sudden infrastructure resets. Work on startups that solve immediate compliance or operational losses.

How to validate your startup to see if it will work or not?

Validate your startup by mapping the specific workflow friction (who feels it, why it is broken, and what it costs them) and tracking the volume of developer and community discussion around it. That's Missing aggregates these validation confidence scores for you.

Is there an AI tool to validate business ideas?

Yes, That's Missing operates as an automated validation and scanner engine, crawling global policy changes, news, and developer discussions to map out validated business ideas and compute validation confidence levels.

GovTech OPPORTUNITY ANALYSIS

Build SovereignAI Revenue Engine, a legal engineering + SaaS platform that enables governments to auto-negotiate, enforce, and audit AI revenue-sharing agreements with labs (OpenAI, Anthropic, Meta) via smart contracts and jurisdiction-aware compliance engines. The platform would deploy AI Revenue Pools (redirecting 3-5% of enterprise revenue to SWFs), integrate with cloud APIs (AWS, Azure, Google Cloud) for usage-based payments, and provide real-time transparency dashboards for economic impact.

Validated on That's Missing platform | Status: Active Opportunity

Market Catalyst & News Trigger

"OpenAI proposed donating 5% of its equity to a US sovereign wealth fund"

        Source: TechCrunch 
        | Published: 7/2/2026
      

The Workflow Friction

Governments globally are grappling with how to ensure public benefit from AI advancements without stifling innovation. Current models rely on voluntary contributions or regulatory mandates, which are either ineffective or politically contentious. The financial and operational cost of inaction includes lost revenue for public funds, lack of transparency in AI-driven economic gains, and potential public backlash against perceived corporate overreach. Sovereign wealth funds (SWFs) and public benefit corporations lack the legal and technical infrastructure to enforce, audit, and monetize AI revenue-sharing agreements at scale.

Problem Summary

Real-world problem signal validation.

One-Shot MVP Builder Blueprint (48 Hours)

A dashboard showing: (1) **AI Revenue Pools**: Pre-negotiated agreements with AI labs displaying real-time redirected revenue (e.g., 'Norway SWF: +$2B/year'); (2) **Jurisdiction Compliance Engine**: Auto-adjusted revenue splits based on local laws (e.g., 'EU: 5% allowed; India: 3%'); (3) **Cloud Usage Tracker**: Integration with AWS/Azure APIs to auto-calculate usage-based payments (e.g., 'AWS GovCloud: $120M/month—redirect 5%'); (4) **Public Benefit Dashboard**: Real-time economic impact (e.g., 'Norway: Funds 100% of education budget'); (5) **Safe Harbor Mode**: Auto-redaction for sanctioned countries (e.g., 'Russia: Access granted with 80% revenue redacted').

Recommended Developer Tech Stack

Solidity
React
Next.js
AWS GovCloud
Chainlink
PostgreSQL