01 / Start simply
A useful first step
Personal is being developed to help people choose, install, and use local AI through one clear application.
About InHouse Compute
AI should fit the way you want to work.
InHouse Compute is building toward a simpler way to use AI on your own terms: start with a local model on a personal computer, or shape a private system around the needs and infrastructure of an organization.
One idea, from a first model to a working system.
The goal is to make private AI approachable without hiding the choices that matter: where it runs, what it can access, and who remains in control.
02 / Keep control
Privacy with choices
Local operation can keep conversations on your device. The wider product vision makes data and infrastructure boundaries understandable.
03 / Go deeper
Room to shape it
Organizations can work with InHouse Compute on deployment, integration, and a clear operating handoff for their own environment.
The Personal application is in development. Public downloads, supported configurations, and release details will be shared when they are ready.
The company
Built from Austin, Texas.
InHouse Compute was founded by Kyle Coutray. The enterprise work today focuses on private AI for document-heavy industrial workflows: approved manuals, procedures, service knowledge, and the people responsible for operating them.
Each engagement starts with the real workflow and its constraints. The deployment boundary, access, backups, support, and ownership are made explicit, with an operating record the customer or its IT partner can use after handoff.
See current enterprise servicesKeep the path open
Personal and Enterprise serve different needs.
Personal is the developing local-AI application. Enterprise is the current service path for organizations that need help evaluating, deploying, or adapting private AI. Both put control of the models, data, and infrastructure closer to the people using them.