Khroma
The AI-powered color discovery tool that learns your aesthetic preferences for infinite design inspiration.
Personalized AI color modeling for professional designers and brand architects.
Khroma is a sophisticated AI-driven color discovery tool that leverages a personalized neural network to understand a designer's aesthetic preferences. Unlike traditional generators that rely on fixed mathematical ratios or popular trends, Khroma requires an initial training phase where users select 50 colors to seed the model. By 2026, its architecture has evolved to utilize a proprietary weighting algorithm that balances color psychology with functional accessibility requirements (WCAG 2.1). The platform functions as an extension of the designer's subconscious, generating an infinite stream of palettes, gradients, and typography pairings that are mathematically tuned to the user's specific 'taste profile.' Its technical superiority lies in its ability to handle semantic searching, allowing users to query colors by mood, temperature, or industry-standard keywords. As of 2026, it remains a critical edge-computing application in the design space, processing model inference locally to ensure privacy and low latency while providing high-fidelity hex, RGB, and CSS outputs for seamless integration into Figma, Adobe Creative Cloud, and web development environments.
Uses a localized machine learning model to assign weights to color values based on a 50-point user training set.
The AI-powered color discovery tool that learns your aesthetic preferences for infinite design inspiration.
Realistic procedural graphic effects for high-precision design workflows.
Professional-grade Text-to-SVG and Raster-to-Vector generation powered by semantic path-tracing AI.
Precision Automated Vectorization: Transform Bitmaps into Clean, Scalable Graphics Instantly.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Natural Language Processing (NLP) layer that maps descriptive adjectives to color hex ranges.
Real-time generation of color pairings through a generative adversarial network (GAN) framework.
On-the-fly contrast ratio calculations between foreground and background elements.
Intelligently calculates transitions and stop points for two-tone and multi-tone gradients.
Uses K-means clustering to extract dominant and accent colors from uploaded images.
Generates custom code snippets including CSS, SASS, and JSON for developer handoff.
Avoiding cliché color combinations and finding unique brand signatures.
Registry Updated:2/7/2026
Ensuring mobile app interfaces are readable and accessible.
Sourcing non-traditional gradients for digital illustrations.