Pearme is an AI‑powered mobile platform that translates users’ real‑time mood inputs into a “Fruit Identity” archetype and generates outfit recommendations from their existing closet and curated new items. The app imports inventory via photos or manual entry, prioritizes sustainable re‑styling before suggesting purchases, and includes a community hub for mood‑based style sharing. Secure cloud syncing ensures privacy across iOS and Android devices.
Funding
Funding not disclosed
Founders
Product
Problem
Consumers often lack a cohesive way to translate fluctuating moods and personal identity shifts into practical wardrobe choices, leading to over-purchasing, underutilized closet items, and a disconnect between style and emotional wellbeing.
Solution
Pearme delivers an AI‑powered styling platform that maps a user’s current emotional state to a “Fruit Identity” archetype, generating personalized outfit recommendations from existing closet pieces and curated new additions. The mobile app captures mood inputs, analyzes them with a proprietary recommendation engine, and surfaces outfit options that align with the identified archetype. By integrating users’ inventory data, the system suggests sustainable re‑styling routes before proposing new purchases, helping users maintain a dynamic yet eco‑conscious wardrobe. Community features enable peer mood check‑ins and shared style inspiration, reinforcing personal expression while fostering a values‑aligned network. All interactions are processed through secure cloud services, ensuring privacy and seamless cross‑device synchronization.
Target Audience
The primary users are fashion‑savvy individuals who seek emotionally resonant, sustainable styling solutions, as well as eco‑conscious consumers who want to maximize the utility of their existing wardrobes.
Features
- AI-driven recommendation engine that translates real‑time mood inputs into a Fruit Identity archetype and corresponding outfit suggestions.
- Automatic closet inventory import via photo capture or manual entry, enabling the system to prioritize existing garments for re‑styling.
- Sustainable styling algorithm that ranks outfit combos based on reuse potential before recommending new items, reducing unnecessary purchases.
- Emotion‑first UI that prompts users to select their current feeling, feeding into the model for context‑aware styling.
- Community hub for mood‑based style check‑ins, allowing users to share outfits, receive peer feedback, and discover trend clusters within the Fruit Identity framework.
- Cross‑platform mobile application (iOS & Android) with offline caching and secure end‑to‑end encryption for personal data.
- API integration points for third‑party retailers to surface compatible new pieces directly within the app’s recommendation flow.