Select the context.
Choose the working files that matter to the task. Your whole computer is not a prerequisite.
Make your knowledge useful. Keep the context intentional. Build with a person at the center.
A focused starting point for private AI: selected files, a defined question, and a result you can review.
Choose the working files that matter to the task. Your whole computer is not a prerequisite.
Use the pilot to ask questions against selected knowledge and develop a working answer.
Review the answer against the material. Keep consequential decisions with a person.
The TKS pilot has been exercised on local NVIDIA hardware and a separate private cloud deployment. Access stays deliberate; cloud compute runs on demand.
Read the development announcement ↗NVIDIA Laptop GPU · verified inference
NVIDIA cloud GPU · private access
Qwen3:4b with Ollama
Three responsibilities for better work. Tri-Core is our approach to synthesis, review, and execution.
Frame the question, define the goal, and turn scattered context into a coherent plan. The first discipline is deciding what matters.
The current pilot runs on conventional NVIDIA hardware. Direct OpenAI, Gemini, and Claude API integrations are future work; no quantum computing service is offered.
This public site introduces the pilot and receives inquiries. Private workspace access is arranged separately. Tell us about your use case below.
No. Browsing this website does not connect your computer, upload its files, or give a model access to it. A private workspace uses explicitly selected context.
The current private AI pilot uses Qwen with Ollama. The broader TKS workflow uses development and planning tools, while direct connections to additional model APIs remain separate integration work.
A small, clearly defined question over a limited set of working documents. Start with non-sensitive sample material and define how a useful answer will be checked.
Tell us what you are trying to understand, organize, or improve. We will start with the problem.
lado@lado-rigvava.com ↗