Private inference platforms and AI-driven products, engineered on infrastructure the client controls. We treat AI as a systems problem first — and a product problem second.
Language model serving, speech transcription, and image generation running on dedicated GPU infrastructure — with no dependency on third-party inference APIs and no data leaving the environment.
GPU-accelerated transcription with Whisper-class models, and machine-learning-driven media indexing and search across large libraries.
Products designed around a defined outcome and an explicit intervention logic. The mechanism is built first; the interface is built around it.
Voice-led interaction for products where lower friction and accessibility matter more than a chat box.
LupOS Core operates a GPU-accelerated inference platform as part of its reference infrastructure — language model serving, transcription, and image generation — entirely within an environment we control. It is the same platform architecture we deploy for clients.
A voice-first AI companion for nicotine cessation, built around the Wave Protocol — a structured craving-intervention framework designed before the interface — for adults aged 18–28 with light-to-moderate use.
Exploratory work on packaging private inference and reference content for environments with limited or no connectivity.
Where AI can carry real weight in your operation, what it needs to run privately, and what it would cost — before anything is built.
A private inference platform designed, deployed, and hardened on infrastructure you control.
Design and engineering of an AI-driven product, from intervention logic through interface and operation.
Tell us what you're running, what you're planning, and where it's fragile. We'll come back with a clear read and a plan.