An AI stylist that knows what a woman will actually wear.

You stop asking the model and start constraining it. On ALIFF, modesty rules — coverage, layering, hijab and accessory logic — live in a structured rule layer that generated outfits are filtered against, not in a prompt the model may or may not honour. Prompt instructions give you compliance most of the time, and in a product where one wrong output costs the user's trust, most of the time is a failure mode. The same pattern applies to any AI feature with a hard boundary: legal, medical, brand or cultural.

An AI feature added to an app you already have starts around $8k. A full AI-assisted product like ALIFF — generation, an image processing pipeline, a rule engine, quota tracking and live subscription billing across both stores — is a larger scope, and we quote it fixed after a free scoping call rather than by the hour. You get a number tied to a written scope, not a range.

Only if you process them first. Raw camera-roll photos are inconsistent — bad light, busy backgrounds, items on hangers — and feeding them straight to a model gives you unreliable tagging and unusable results. ALIFF runs every upload through a flat-lay pipeline before anything AI touches it, so the model always sees clean, consistent input. That preprocessing step is usually the difference between an AI feature that works in a demo and one that works in a user's hands.

You design the economics with the feature, not after the first invoice. ALIFF meters at the AI layer — weekly chat, weekly generation and lifetime upload quotas — caches repeated work, and streams responses so users perceive speed without extra inference. The quota wall is also where the free trial triggers, so cost control and the upgrade moment are the same mechanism.

Yes, and we build it early. ALIFF ships through RevenueCat over Apple In-App Purchase and Google Play Billing, with a seven-day trial, auto-renewal, receipt validation and purchase restoration. Billing is the part founders defer and then discover is a project of its own — we treat it as part of the MVP so the revenue path is proven, not assumed.

It will if the parts reviewers actually check are built properly. ALIFF cleared both stores with in-app purchase configured through RevenueCat, restore-purchase implemented, account deletion available in-app, and data-safety and privacy declarations completed for photo and personal data handling. Most AI app rejections come from those four things rather than from the AI itself — we treat store submission as a build task with its own acceptance criteria, not as paperwork at the end.