# AI and Decision Systems
Production-minded AI that helps teams classify, score and act while keeping people accountable for consequential decisions.
We build decision systems that combine useful automation with the controls, evidence and expert judgement required for production use.
## Beyond model demos
A model result is not an operating decision. Production systems must manage source evidence, uncertainty, exceptions, permissions and the point at which a person reviews or overrides an output.
## Designed for accountable decisions
We combine data pipelines, model services, workflow software and review interfaces so teams can classify, prioritise and score work without losing traceability.
## Measured in the workflow
Performance is judged through decision quality, cycle time and operational adoption, with monitoring and escalation designed around the real consequences of error.
## Capabilities
- [Applied AI Engineering](/applied-ai-engineering)
- [Data and Analytics Engineering](/data-analytics-engineering)
- [Software and Product Engineering](/software-product-engineering)
- [Platform and Cloud Engineering](/platform-cloud-engineering)
## Who it's for
- [AI systems for operations leaders](/for/ai-systems-for-operations-leaders)
## Frequently asked questions
### What is an AI decision system?
It is software that uses AI to classify, score or prioritise work, then puts that result inside the workflow where the decision is made. It records the evidence behind each output, flags uncertain cases and gives a person what they need to accept, change or reject the recommendation.
### How do you keep people accountable for decisions?
We agree with you which decisions the system can make alone and which need a person. Uncertain or high-impact cases go to a reviewer and every override is recorded with a reason. The audit trail shows who decided what and on which evidence.
### How do you measure whether the system works?
Accuracy on a test set is only the start. We also track decision quality in live use, how long cases take, how often reviewers override the system and what errors cost. We agree these measures before the build so the results are clear.
### Can you use our existing data and models?
Yes. Most projects start from data you already hold, and we can work with existing models or vendor services. We check data quality and access early, because gaps there limit what any model can do.
### How do you handle sensitive data?
We design data handling around your obligations from the start: where data is stored, who can see it, what is sent to third-party models and how long it is kept. Where needed, we use models hosted in your own environment.
HTML: https://rodan.io/what-we-build/ai-decision-systems