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.

AI/ML OPPORTUNITY ANALYSIS

Build 'FraudGuard AI'—a $10K/year SaaS platform for Indian mid-market banks and fintechs that deploys edge AI for real-time fraud detection and auto-generates RBI-compliant compensation reports. The platform would: 1) Use Gemini Nano on-device to analyze transaction patterns (e.g., 'User X swipes ₹5K at 3AM—flag as grooming for scam'); 2) Integrate with NPCI’s UPI and RBI’s e-Surveillance APIs to auto-block suspicious transactions; 3) Provide a 'Fraud Compensation Module' to auto-generate RBI reports (e.g., '₹20K fraud—compensation issued within 24h'); 4) Offer a 'Regulatory Heatmap' showing fraud hotspots by district (e.g., 'Mumbai: 45% of scams target senior citizens').

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

Market Catalyst & News Trigger

"RBI Governor Sanjay Malhotra states 'rate hike talk is premature' amid weak monsoon concerns, but mandates stricter e-banking fraud compensation rules"

        Source: The Times of India 
        | Published: 6/24/2026
      

The Workflow Friction

Indian mid-market banks and fintech startups cannot afford enterprise-grade fraud detection systems (e.g., SAS Fraud Management, $500K/year). RBI’s new rules mandate compensation up to ₹25,000 for e-banking frauds, but smaller players lack real-time transaction monitoring, behavioral AI, or automated dispute resolution. Current solutions are either manual (e.g., Excel-based chargeback tracking) or rely on outdated rule-based engines (e.g., 'flag transactions >₹1L'), leading to false positives and regulatory penalties. Fraud losses cost Indian banks $2.5B annually (Reserve Bank of India, 2025).

Problem Summary

Real-world problem signal validation.

One-Shot MVP Builder Blueprint (48 Hours)

A dashboard showing: 1) Real-Time Fraud Alerts: 'User Y sent ₹10K to unknown account—flagged as pig-butchering scam'; 2) RBI Compensation Tracker: '₹15K fraud detected—auto-generated Form 42 submitted to RBI'; 3) Fraud Heatmap: 'Delhi: 30% of scams involve fake customer care calls'; 4) False Positive Feedback Loop: 'Allow users to mark alerts as 'safe' to improve model accuracy.'

Recommended Developer Tech Stack

Flutter
Gemini Nano
Firebase
NPCI UPI API
RBI e-Surveillance API