What we're exploring
Three connected areas. Each is useful on its own, and more useful together.
Practical AI
Applying language models and automation where they measurably save time or improve decisions.
The interesting work in AI is rarely the model itself. It is choosing the right problem, connecting the model to real data and tools, and keeping a person in the loop where judgment matters. We are exploring assistants, document and workflow automation, and retrieval over an organization’s own knowledge.
Examples we’re exploring
- Assistants that work with an organization’s own documents
- Automating repetitive intake, sorting, and summarizing
- Evaluating whether AI is the right tool before building
Software
Web and mobile software that is fast, maintainable, and built around how people actually work.
AI features only help when the software around them is dependable. We favor small, well-structured applications, static and edge-hosted sites that are fast by default, and plain integrations that are easy to maintain long after launch.
Examples we’re exploring
- Fast, accessible websites and web applications
- Mobile experiences and device integrations
- APIs and integrations between existing tools
Connected hardware
Sensors and devices that bring real-world signals into software people can act on.
Some of the most useful data is not in a database yet. It is sound levels, temperatures, motion, or location. We are exploring how inexpensive connected devices can capture those signals and how software and AI can turn them into something useful.
Examples we’re exploring
- Sensor prototypes and data collection
- Dashboards and alerts built on device data
- Edge processing where connectivity is limited
From question to working system
See the proposed approach that ties these areas together.