Development / tools / infrastructure
Learn by building. Evaluate what happens.
Practical exploration of AI-assisted work and the systems behind it.
Tools and workflows
The work includes assistant and workbench prototypes, workflow automation, and experiments with retrieval and graph-based memory. The aim is to understand where AI helps and what people need to inspect or challenge its output.
Infrastructure and local control
Local-model infrastructure provides a way to explore model behavior, data boundaries, and the operational work behind AI systems. Reliability, security, and evidence matter alongside capability.
Current stage
These are areas of active research and development. Public project descriptions and demonstrations will be added when there is specific work ready to share.