Research
Understanding the problem
- AI systems and agents
- Evaluation methods
Neobolt ● Systems
The systems around the model decide whether AI can be trusted.
Safety by design
Control what AI can see
- ● Access to data is explicit, scoped, and reviewable
- ● Security considered from the first design decision
- ● Permissions defined before an AI acts
“A model that can act needs limits that are designed, tested, and visible.”
Built for real environments
Integrates with real software
- ● Connections to tools and APIs
- ● Role-based permissions
- ● Logging and monitoring
“Deploying AI is an engineering problem as much as a model problem.”
Stay reliable
Evaluated before trusted
- ● Tests that reflect real tasks
- ● Failure detection built into the system
- ● Human review where it matters
Designed for oversight
Built to be inspected
Capable models are widely available. Reliable systems around them are not.
How we work
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Engineering
Building the systems
- Orchestration and tool use
- Integration with real software
Safety
Constraining and checking them
- Permissions and oversight
- Logging and monitoring