Solutions / AI systems
AI system design, implementation and evaluation
Useful AI needs more than a model response. It needs the right context, a clear place in a workflow and a way to tell whether it is performing as intended. Lucci works across those decisions, the implementation and the evaluation.
Where this work helps
This work fits teams exploring a specific AI use case, integrating a model or agent into an existing process, or reviewing the quality and reliability of a system they already have. We start with the task and the consequences of an incorrect result.
What we examine
- The task, the available information and where AI is appropriate
- Model integrations, agent tools and the flow of context
- Quality, reliability and the cases that need human review
- Oversight, failure handling and operational handoff
What the work can deliver
- A defined use case and an implementation or evaluation scope
- A system design showing context, actions and human decisions
- Working model integrations or AI-enabled tools where agreed
- Evaluation findings, documented limitations and a practical handoff
How we approach it
We define what success means for the task, design or examine the system, and check it against relevant examples and failure cases. Building and evaluation can be scoped together or as a review of an existing system.
Evaluation findings apply to the conditions and examples tested. They do not establish universal accuracy, a safety certification or performance in settings that have not been evaluated. Research publications are available separately through Lucci Labs.
Related work
UX audits and digital product design · Workflow assessment and automation
Discuss the work you want to improve.
We agree on the scope and deliverables before a project begins.