A better answer to what should I wear?
Fraghab has separate intelligence for the choice in front of you: an everyday recommendation, an outfit, a week, a trip, or the next bottle you are considering. Every one begins with your real shelf.
What's your vibe?
Set the mood — or skip to use defaults.
Describe the moment. Get a ranked answer you can inspect.
The core suggester turns mood, time, occasion, weather, rotation, feedback, and availability into ranked collection picks — with reasons instead of a black box.
- Three-step recommendation flow — set Vibe, Scene, and inventory intent, or leave context open for the engine to fill from current conditions.
- Natural-language query — write what you want in plain language; the parser can recognize moods, weather, occasions, reference scents, avoidance, and exploration signals.
- Outfit matching — upload a JPEG, PNG, or WebP look and the vision flow returns collection picks with an outfit-aware rationale.
- Actionable results — quick-log a pick, inspect its score, ask why it won, skip it with a reason, or save it as a sample to try.
“Something smoky but polished for a cold dinner downtown.”
2 Minutes to Midnight
The Fragrance
The darker woods hold up in cool air, while the polished drydown fits dinner without crowding the room.
A week and a trip are different decisions.
Fraghab treats them that way: one flow builds a considered seven-day rotation and another builds a destination- and forecast-aware packing list.
- Weekly planner — starts with editable per-day occasions and connected calendar context, then balances weather progression, rotation, variety, feedback, and unworn bottles.
- Lock, swap, and log — keep a planned bottle in place, choose an alternate, examine the score and reasons, then log the wearing when the day arrives.
- Travel mode — search a destination, set the trip dates, and receive a forecast-aware daily packing rotation with substitutes and quick logging.
Weekly planner
Plan your week, then get your picks.
Travel mode
Pack the perfect rotation for your trip.
The buying agent evaluates the gap, not just the want.
What to Buy is a dedicated wishlist intelligence workflow. It considers your intent, budget, collection overlap, active wishlist, price research, and discovered candidates before it recommends a purchase.
- Intent-led recommendations — tell the agent what you want next or ask it to work from your current wishlist and budget.
- Live research and comparison — the agent can assess prices and candidates, then explain the tradeoffs and offer refinements rather than a single unsupported pick.
- A decision trail — review past buying suggestions, save a candidate to the wishlist, and use Try Before You Buy when a sample is the smarter next move.
Your shelf is strong in sweet amber. The better addition adds dry woods and incense without repeating the same dense vanilla profile.
Counterplay
Mind Games · est. $168
Best balance of contrast, winter versatility, and price. The incense profile fills a real gap without crowding what you own.