Build
personalized AI.
Using our platform, AI now understands who your users are, what they want, and how they want it.
Galya’s taste infrastructure uses structured preference signals to give AI products the context they need to understand and serve their users, without relying on personal data.
Content or catalog entities
Products, properties, content, and inventory indexed by intuitive attributes.
Customer interaction signals
Scroll depth, dwell time, click patterns, and return behavior.
Customer Intelligence
See your users the way your AI should.
The Galya dashboard shows you how your audience interacts with your content (interest signals, behavior patterns, and audience clusters) so you know who you’re actually building for, and can take action on that intelligence.
No data goes to waste.
Taste-Based Reranking
The right result, for the right person, every time.
Galya reranks your search and discovery results by audience signal, with no behavioral history required.
Better matches, higher conversion, less friction, no cold-start.
Agent Context Injection
Your AI gets the context. Your users skip the explanation.
Inject structured audience intelligence directly into your AI, so it makes better decisions from the first interaction, not the tenth.
Compliant at its core
Galya’s models operate without any personally identifiable information (PII), ensuring complete compliance with major data protection regulations like GDPR and CCPA.
@galya/sdk
Tag your UI in minutes. The browser SDK captures how users actually engage (dwell, scroll depth, revisits) and sends signals to Galya automatically.
@galya/agents
Search, rerank, ask, explain. All relative to a user or entity. One typed REST client to make every layer of your product taste-aware.
Agent Tools
Every Galya method ships as a galya_* tool for function-calling models. Drop taste intelligence into any LLM loop, no URL wiring, no custom prompting.
Taste, injected at inference.
Signals come in, Galya computes taste context, and your AI responds in kind — live, at inference, with no personal data.
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Ready to give your AI taste?
Book a demo and see your first Taste Graph composed live, from cold-start to a callable preference layer.