Expert agent training
An AI interview that turns real experience into a structured playbook, and a training loop where the expert’s corrections become lessons the agent follows. Built on Claude models with structured outputs, refusal fallbacks and explicit timeouts.
AI infrastructure
Multi-model orchestration across vision and language providers. Cost-aware routing, prompt caching, and observability built in from day one.
Computer vision
Garment detection, body keypoint estimation, virtual try-on, and image-to-attribute pipelines that power our wardrobe intelligence.
Cloud architecture
Serverless inference workers, managed Postgres with proxy pooling, and asynchronous job queues. Designed to scale gracefully from one user to millions.
Mobile platforms
React Native + Expo with native modules where it matters. OTA updates for fast iteration and EAS builds for store releases.
Real-time media pipelines
Upload preflight, GPU-accelerated image processing, deduplication, and content-addressable storage, built for premium consumer media.
Three things we don’t compromise on.
Cost-aware AI
Model routing and prompt caching keep inference economics sustainable.
Craft in the experience
AI is the engine; design is the experience. Both deserve care.
Privacy as engineering
Per-user data isolation and explicit encryption. Privacy is engineering, not a checkbox.