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.
Point a long-context reviewer at contract analysis, and let people review output instead of producing it. Aimed at home care schedulers, starting from data the business already produces.
Point a vision model at field reporting, and let people review output instead of producing it. Aimed at home care schedulers, unbundling the one module people actually use.
Quoting & estimating handled by a forecasting model, with a human signing rather than writing. Aimed at home care schedulers, so the work stops following people home.
A reconciliation engine that sits beside the existing system, reads what it already produces, and closes margin monitoring. Aimed at home care schedulers, unbundling the one module people actually use.
A narrow anomaly detector scoped to vendor management alone — no platform, no migration, no six-month rollout. Aimed at home care schedulers, taking the phone queue off a human entirely.
A reconciliation engine that handles vendor management end to end and hands a human the exceptions rather than the queue. Aimed at home care schedulers, replacing the spreadsheet that currently holds it together.
A narrow document parser scoped to intake & triage alone — no platform, no migration, no six-month rollout. Aimed at home care schedulers, taking the phone queue off a human entirely.
A narrow workflow engine scoped to onboarding alone — no platform, no migration, no six-month rollout. Aimed at home care compliance leads, unbundling the one module people actually use.
Point an optimisation engine at dispatch, and let people review output instead of producing it. Aimed at home care compliance leads, holding service constant on a smaller team.
Collections handled by a forecasting model, with a human signing rather than writing. Aimed at home care compliance leads, holding service constant on a smaller team.
A document parser that sits beside the existing system, reads what it already produces, and closes incident reporting. Aimed at home care compliance leads, built for one person, not a department.
Training & competency handled by a retrieval engine, with a human signing rather than writing. Aimed at home care compliance leads, finding what the inspector would find, first.
Training & competency handled by a retrieval engine, with a human signing rather than writing. Aimed at home care compliance leads, replacing the spreadsheet that currently holds it together.
A retrieval engine that sits beside the existing system, reads what it already produces, and closes training & competency. Aimed at home care compliance leads, built for one person, not a department.
Point a forecasting model at lead qualification, and let people review output instead of producing it. Aimed at home care compliance leads, proving value before anyone signs anything.
Point a document parser at grant & funding tracking, and let people review output instead of producing it. Aimed at home care compliance leads, catching the error before it becomes a change order.
Point a geospatial model at site selection, and let people review output instead of producing it. Aimed at home care compliance leads, at a tenth of what the enterprise suite charges.
Site selection handled by a geospatial model, with a human signing rather than writing. Aimed at home care compliance leads, writing down what only one person knows.
An anomaly detector that sits beside the existing system, reads what it already produces, and closes margin monitoring. Aimed at home care compliance leads, closing the loop while everyone is asleep.
Vendor management handled by an anomaly detector, with a human signing rather than writing. Aimed at home care compliance leads, charging only when it actually works.
Vendor management handled by a reconciliation engine, with a human signing rather than writing. Aimed at home care compliance leads, taking the phone queue off a human entirely.
Point a reconciliation engine at vendor management, and let people review output instead of producing it. Aimed at home care compliance leads, catching the error before it becomes a change order.
Scheduling handled by a forecasting model, with a human signing rather than writing. Aimed at legal solo practitioners, starting from data the business already produces.
Document review handled by a document parser, with a human signing rather than writing. Aimed at legal solo practitioners, writing down what only one person knows.