TasteBrain TasteBrain / Docs
Quickstart API Reference GitHub

Getting Started

  • Introduction
  • Quickstart
  • Core Concepts

Level 0: The Model

  • Overview
  • Model Architecture
  • Taste Vectors

Level 1: SVK Primitives

  • Overview
  • Cross-Modal Search
  • Prism Service
  • Mosaic Service
  • Shopkeep Service

Level 2: Persona Services

  • Overview
  • Windows & Curation
  • Sentiments
  • Tasteboards
  • Context Pipelines
  • B-Shop & B-Side

Examples

  • InstaShop
  • Streams
  • BookTaste
  • Dress Code

Reference

  • API Reference
  • SDK Documentation
  • Claude Code Plugin
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TasteBrain Foundations

The global geometry of taste

A transformer-based, multimodal model for understanding human taste and aesthetic preference. Foundation-derived from Qwen-Omni, trained on ~20M curated product images across ~7M products.

128-dimensional multi-vector embeddings. Lightweight per-user taste models. Weekly-refreshed crawling across retail, restaurants, music, and culture.

Get Started Documentation
Level 0

The Model

Qwen-Omni backbone with fine-tuned attention layers, custom projector, and 128-dim multi-vector embedding space.

Level 1

SVK Primitives

Stateless API primitives — Prism and Shopkeep — for cross-modal search, sentiment reranking, and brand matching.

Level 2

Persona Services

Per-user taste models, Windows, Sentiments, Tasteboards, context ingest pipelines, and retailer intelligence.

Example Applications

InstaShop

Instagram aesthetic analysis mapped to curated product sets.

insta.bestomer.com

Streams

Infinite scroll product discovery with image upload and personalization.

streams.bestomer.com

BookTaste

Literary prose mapped to aesthetic product matches.

ishmael.bestomer.com

Dress Code

Wedding event parsing into complete looks and shoppable categories.

examples/dresscode

The SVK is optimized for LLM-assisted development. Install the Claude Code plugin and start searching in minutes.

Start building