Visual intelligence.
Privacy-first.
On-device computer vision pipelines and a licensable similarity engine for fashion and retail. Add visual search, recommendations, and private personalization without uploading photos.
encrypted
Built for the future of privacy
Everything runs client side. Your images never leave your device.
Client-side inference
Run optimized ONNX models on device with WebGPU/WASM for real-time detection and embedding generation. Zero server uploads.
Vector similarity engine
512D embeddings and pgvector-compatible search for "find similar" and cross-catalog matching with low-latency results.
Privacy by design
Only embeddings and user-validated metadata are shared. Reduce data liability while preserving personalization and conversion uplift.
Retail SDK & API
Lightweight SDKs and REST APIs for easy integration into e-commerce platforms, AR try-ons, and discovery features.
Model ops & export
Production-ready model export (PyTorch → ONNX), progressive loading, quantization, and cross-platform optimization.
Encrypted compute roadmap
Research into obfuscated client-server compute and homomorphic encryption to enable encrypted inference workflows.
About Raincoat Labs
We build modular visual intelligence edge-AI that lets developers add vision-powered features while keeping user data private. Our first production use case is Raincoat, a consumer app that demonstrates the tech and drives early adoption.
Interested in a pilot or SDK?
Request early access