AltF Ideas holds 117,264 startup ideas across 61 industries, each scored 0–100 on demand, moat, monetisation, feasibility, timing and open field. The 12,000 highest-scoring have full dossiers with market size, competitor archetypes, risks, and a four-step build path. Sorted by opportunity score, best first.
A document parser that sits beside the existing system, reads what it already produces, and closes document review. Aimed at retail store managers, built for one person, not a department.
A long-context reviewer that sits beside the existing system, reads what it already produces, and closes RFP response. Aimed at retail owner-operators, holding service constant on a smaller team.
A narrow forecasting model scoped to scheduling alone — no platform, no migration, no six-month rollout. Aimed at retail merchandisers, charging only when it actually works.
A narrow retrieval engine scoped to risk assessment alone — no platform, no migration, no six-month rollout. Aimed at retail ops teams, replacing the spreadsheet that currently holds it together.
A narrow forecasting model scoped to scheduling alone — no platform, no migration, no six-month rollout. Aimed at e-commerce marketing leads, closing the loop while everyone is asleep.
Point a forecasting model at pricing, and let people review output instead of producing it. Aimed at e-commerce marketing leads, closing the loop while everyone is asleep.
Point a retrieval engine at knowledge capture, and let people review output instead of producing it. Aimed at retail owner-operators, taking the phone queue off a human entirely.
A reconciliation engine that sits beside the existing system, reads what it already produces, and closes reconciliation. Aimed at retail owner-operators, charging only when it actually works.
A geospatial model that sits beside the existing system, reads what it already produces, and closes site selection. Aimed at retail owner-operators, catching the error before it becomes a change order.
A document parser that sits beside the existing system, reads what it already produces, and closes document review. Aimed at retail owner-operators, holding service constant on a smaller team.
Invoicing handled by a document parser, with a human signing rather than writing. Aimed at retail merchandisers, going after the low-value tail everyone else skips.
Point an autonomous agent at scheduling, and let people review output instead of producing it. Aimed at retail merchandisers, proving value before anyone signs anything.
A retrieval engine that sits beside the existing system, reads what it already produces, and closes contract analysis. Aimed at retail merchandisers, replacing the spreadsheet that currently holds it together.
Point a voice agent at incident reporting, and let people review output instead of producing it. Aimed at retail merchandisers, replacing the spreadsheet that currently holds it together.
Collections handled by a forecasting model, with a human signing rather than writing. Aimed at retail ops teams, taking the phone queue off a human entirely.
A reconciliation engine that handles margin monitoring end to end and hands a human the exceptions rather than the queue. Aimed at e-commerce owner-operators, unbundling the one module people actually use.
Point a document parser at RFP response, and let people review output instead of producing it. Aimed at e-commerce owner-operators, starting from data the business already produces.
A narrow document parser scoped to quoting & estimating alone — no platform, no migration, no six-month rollout. Aimed at e-commerce ops teams, so the work stops following people home.
RFP response handled by a retrieval engine, with a human signing rather than writing. Aimed at e-commerce ops teams, starting from data the business already produces.
A narrow retrieval engine scoped to knowledge capture alone — no platform, no migration, no six-month rollout. Aimed at e-commerce ops teams, starting from data the business already produces.
Point a voice agent at knowledge capture, and let people review output instead of producing it. Aimed at e-commerce ops teams, charging only when it actually works.
Point a document parser at payroll verification, and let people review output instead of producing it. Aimed at e-commerce ops teams, proving value before anyone signs anything.
Site selection handled by a forecasting model, with a human signing rather than writing. Aimed at e-commerce marketing leads, charging only when it actually works.
A long-context reviewer that handles RFP response end to end and hands a human the exceptions rather than the queue. Aimed at e-commerce marketing leads, so the work stops following people home.