AINAA Edit / Inside AINAA

How AINAA Learns What You Love

By AINAA Editorial. Updated 16 June 2026.

AINAA learns your taste from the signals you give it: likes, dislikes, hides, saved looks, and the words you use in chat. Every action nudges a profile of your colours, fabrics, fits, and occasions, so the more you shop and talk, the sharper and more personal the recommendations become.

What a fashion recommendation engine actually reads

Most shopping feeds treat you as a demographic. AINAA treats you as a set of preferences that change over a season. Underneath the styling, the fashion recommendation engine keeps a taste profile built from real behaviour rather than guesses. It does not need you to fill in a long form. It reads what you do.

The strongest signals are the deliberate ones. When you tap like on a deep wine Banarasi kurta, AINAA registers more than approval of one product. It notes the colour family, the silk weave, the structured fit, the festive occasion, and the price segment, then raises the weight of each of those attributes a little. Save the same look to a collection and the signal is stronger still, because saving signals intent rather than passing interest.

The five signals that build your taste profile

AINAA weighs a handful of clear inputs. Each one teaches it something specific:

• Likes pull your profile toward that piece. Like enough fluid georgette anarkalis and your festive results start leaning drapey rather than rigid.
• Dislikes push it away. A dislike on a heavily embellished lehenga tells AINAA you may prefer cleaner surface work, so it eases off the zardozi and shows you understated chikankari and tonal threadwork instead.
• Hides remove a product from view and quietly mark its attributes as unwelcome for now, which is useful when a colour or cut simply is not for you.
• Saves are the clearest vote of confidence. Saved looks anchor the profile because you chose to keep them, not just glance at them.
• Conversation carries nuance no button can. Tell AINAA you want something for a Udaipur sangeet that is comfortable to dance in, and it reads occasion, climate, and silhouette in one line.

Because all five feed the same model, your taste profile is not a single dial. It tracks colours, fabrics, silhouettes, necklines, sleeve lengths, formality, occasions, and price comfort separately, so AINAA can know you love a high-waisted palazzo without assuming you love every co-ord set it sits in.

Cold start: how AINAA helps before it knows you

A recommendation engine has a problem on day one. With no history, it has nothing to personalise against. AINAA solves this with a short onboarding rather than a blank feed.

When you first arrive, you pick your gender and a few vibes that describe how you like to dress: minimal and tailored, festive and ornate, relaxed indo-western, contemporary western, and so on. Those choices seed an initial profile so your very first results are sensible instead of random. A minimal-leaning shopper sees clean column silhouettes and quiet colours; a festive-leaning shopper sees richer fabrics and brighter palettes from the start.

This seed is deliberately light. It exists to get you a good first impression, then to step aside. Once you have given AINAA a small number of real signals through likes, saves, and chat, your actual behaviour overrides the onboarding guess. The vibes you picked in week one stop mattering the moment your taps and conversations say something more specific.

Steering it yourself with more, less, and hide

You are never stuck with what the engine assumes. Three controls sit on the products AINAA shows you, and each is a direct instruction.

More

Tap more on a piece and AINAA pulls future results closer to it. More on a structured ivory bandhgala tells it to lean into sharp tailoring and ceremonial menswear, so the next set arrives with cleaner lines and a dressier register.

Less

Use less when something is close but not quite. It is a softer signal than a dislike. If the embroidery is heavier than you want or the heel higher than you would wear, less eases that direction back without banishing the whole category.

Hide

Hide takes a product out of your view immediately. It is the quickest way to tidy a feed and, as a side effect, it teaches AINAA which attributes to deprioritise. Hide a few neon bodycon dresses and your results settle into the calmer palette you actually wear.

These controls matter because taste is personal and sometimes contradictory. You might love bold colour in a saree and want it nowhere near your office shirts. The steering tools let you draw those lines, and AINAA holds them per occasion rather than flattening them into one average.

Why your recommendations keep improving

The profile is not fixed at signup. Recent signals carry more weight than old ones, so the engine follows you as your taste moves. A monsoon of relaxed kaftans and flat kolhapuris will not lock you out of structured tailoring when wedding season returns; the newer saves simply take over.

This is also why the quiet, honest answer to "why am I seeing this" usually traces back to something you did. A reason tag on each recommendation points to the colour you favoured, the brand you saved, or the occasion you asked about. If a result feels off, one tap of less or hide corrects course, and AINAA carries that correction into the next conversation. If you would rather just describe what you want, telling AINAA in plain language works as well as any button.