Two products, one principle: the software runs on hardware you own, and your data does not leave your network to make it work.
Hearth is for a person or a household — a single binary that turns a directory into a browser-based workspace with a contained AI agent, and optionally a server the rest of the family signs into.
DistributeX is for a financial firm — a platform for distributed quantitative computing. It ships with working pricing and risk workers, but the point is how easily you add your own: a worker is a table of functions taking JSON and returning JSON, in C++, Python, Java, C# or VBA, and a client is three HTTP calls.
If you want help choosing, deploying, or running either of them, that is what our services are for.
While large enterprises race to adopt AI, the tools that deliver real value remain expensive, complex, and locked behind cloud-only subscriptions or enterprise sales cycles. Most families, schools, public libraries, and community organizations are left choosing between fragmented consumer apps, privacy-invasive services, or tools that require significant technical expertise to set up and maintain.
Hearth (also known as CasaHub) is built to close that gap. It is a complete, pre-configured AI workspace that brings powerful document tools, AI chat, and coding assistance to ordinary users — whether they run it on a Mini PC or Raspberry Pi at home, host it on an inexpensive VPS, or keep their files in familiar cloud storage such as Google Drive, Dropbox, or OneDrive.
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A platform for distributed quantitative computing designed for firms that already have working models and refuse to rewrite them.
DistributeQL solves the core dilemma facing small-to-mid-sized quantitative teams: how to scale battle-tested, thread-unsafe C++ libraries like QuantLib across a cluster and expose them to modern cloud workflows and AI agents—without incurring the multi-month delay and numerical discrepancy risk of a ground-up rewrite.
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