Most AI tools live in the cloud, which means you have to send confidential data outside your control to get the best answers. That becomes a real problem when your private information includes internal documents, source code, or company knowledge that should never leave your environment.
OrigoVisio helps you move AI closer to the source of truth: your own machine and your own infrastructure.
Our Mission
We build local AI systems that let people and companies train models on their own data without giving that data to a cloud provider.
Our goal is straightforward: make private knowledge permanent, reusable, and secure by keeping the model close to the people who own the data.
Why This Matters
Cloud AI has two core limitations. First, sensitive data must be shared with an outside service before the model can answer with full context. Second, the model does not retain your working knowledge unless you keep feeding it back in, and every cloud context window is limited.
That means teams repeatedly re-explain the same business rules, codebase history, and operational knowledge. Valuable context gets lost between sessions, and private information is exposed just to recover it.
For companies working with proprietary code, internal documents, or confidential workflows, this is not a minor inconvenience. It is a structural weakness in the way cloud AI is delivered today.
MemoryPC is the first step in that mission. It lets you download and experiment with local AI directly on your Windows machine.
If your data is confidential across the company, you can train a model locally, share the trained model internally, and let teammates use it for inference without exposing the original source material to the public cloud.
- Local Training on Private Data: Build AI models from your own documents, code, and company knowledge without sending them to a cloud provider.
- Persistent Organizational Memory: Capture the context your team has already built so it can be reused instead of reconstructed for every new prompt.
- Internal Model Sharing: Train once, distribute the model across your company, and support inference use cases without exposing the underlying confidential data.
- Better Answers from Real Context: Improve relevance by grounding the model in the information your team actually uses, not just what fits into a temporary prompt window.
- Windows-Based Experimentation: Start directly on your own machine with MemoryPC and evaluate local AI in a practical, controlled environment.