The intelligent digital closet assistant for sustainable, capsule-based personal styling.
Cladwell is a sophisticated AI-driven personal styling platform designed to solve the 'analysis paralysis' of daily dressing through algorithmic wardrobe optimization. The platform leverages computer vision to catalog user garments, identifying attributes like color, texture, and style category. In the 2026 fashion tech landscape, Cladwell stands out by focusing on the 'circular economy,' using predictive analytics to help users maximize their existing closet utility rather than encouraging new purchases. Its core engine integrates real-time meteorological data with user-specific style profiles to generate daily 'Outfits of the Day' (OOTD). Technically, Cladwell employs a graph-based recommendation system that treats individual clothing items as nodes and stylistic compatibility as weighted edges, allowing it to generate thousands of viable combinations from a minimal set of items. By calculating 'cost-per-wear' metrics and identifying 'closet voids,' Cladwell provides a data-centric approach to personal style, effectively acting as a digital bridge between a user's physical wardrobe and sustainable consumption habits.
Proprietary algorithm that calculates outfit compatibility scores based on color theory, occasion relevance, and historical user feedback.
Accelerating fashion's Industry 4.0 transition through AI-driven design, development, and competitive intelligence.
The premier AI-driven benchmarking and recognition ecosystem for the digital fashion frontier.
End-to-end 2D/3D CAD platform for fashion and textile production powered by AI-driven nesting and simulation.
AI-driven trend forecasting and consumer intelligence for the global creative industry.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Real-time API calls to weather services to filter wardrobe recommendations by temperature, precipitation, and humidity.
Calculates the economic value of each garment by dividing purchase price by the number of times logged in the app.
A sub-setting tool that isolates a specific number of items to maximize permutations for a set period.
Algorithm that selects a subset of the wardrobe for a trip based on destination weather and trip duration.
Identifies missing categories or colors that would unlock the highest number of new outfit combinations.
Computer vision model that automatically classifies garment type, sleeve length, and neckline from a single photo.
Reducing the cognitive load of choosing clothes every morning.
Registry Updated:2/7/2026
Identifying clothes that are never worn and can be donated.
Avoiding over-packing while ensuring enough outfits for a trip.