Your AI systems work in a demo. Can you rely on them in production?
AI systems combine models, data, tools and, increasingly, agents that execute code and modify resources.
Putting them to work takes more than designing an interaction with a language model: you need to control the data they use, their execution environment, their permissions, their behaviour and their limits.
Stratorys works on the architecture and engineering of these systems.
The questions to resolve
What is the system actually responsible for?
Which decisions does it make or support? Which actions can it execute? In which situations is human validation required?
Which data, models and tools does it rely on?
How do you define the accessible resources, the permissions it needs and the limits of its interactions with external systems?
How do you evaluate its behaviour?
How do you test its outputs and the tasks it performs, identify failures and verify how it behaves in representative scenarios?
How do you secure its execution environment?
How do you limit access to secrets, files, code repositories and system commands, particularly when agents act autonomously?
Our areas of work
AI systems architecture
Workflow design, retrieval and data access, state management, orchestration, integration with existing systems and definition of each component's responsibilities.
Agents, harness & execution environment
Design of the mechanisms that frame model and agent execution: context, tools, sessions, action handling and controls.
Evaluation & observability
Test scenarios, evaluation mechanisms, execution traces and behaviour analysis.
Permissions & security
Access management, isolation, tool control, resource protection and validation mechanisms.
AI runs inside a controlled system
How we can work with you
Analyse
Examine an existing AI architecture, its capabilities, its data access, its permissions and its controls.
Design
Define the target architecture, the system boundaries, the data and tool contracts and the evaluation requirements.
Implement
Support the development of the technical components needed: harness, runtime, retrieval, integrations, evaluations and control mechanisms.
A possible first engagement
AI system architecture and controls review
A targeted technical review of an AI system, an agent or an execution environment to identify the architecture decisions and controls to improve.
Scope defined together: an AI application, a retrieval pipeline, an agent or an environment for autonomous coding agents.
This engagement does not on its own constitute a security guarantee or an exhaustive penetration test.
- Map of components, models, data and tool access
- Analysis of execution boundaries and permissions
- Identified technical risks
- Architecture, evaluation and security recommendations
- Prioritised improvement plan
Let's talk about your AI system
Designing an AI system, preparing it for production or looking to better control its behaviour?
Describe your context and the constraints you are facing.
Talk to Stratorys →