AI Safety & Quality

AI testing means building a test set from real and difficult cases, agreeing what a good answer looks like with your domain experts, then scoring the system before launch and after every change. We track accuracy, safety and edge-case handling as measurable scores rather than opinions. Failing cases are fixed before launch, and the same test set is reused for every future change. This gives you evidence the AI works as agreed, not just a feeling that it does.

Cost depends on how many use cases need test coverage, how much expert review is required, and whether ongoing monitoring is included. We typically scope a fixed-price initial test set and evaluation report before quoting ongoing monitoring as a separate recurring service. Reviewing an existing AI system your team already built is priced similarly to a new build, since the test set work is the same.

Yes, live monitoring tracks answer quality, response time, cost and failures after launch, with alerts sent to the responsible owner when results drift. We retest after every change to instructions, data or the underlying model, plus on a regular schedule in production. This catches quality drops before customers or regulators do. Monitoring dashboards are delivered alongside the initial evaluation report.

We find personal and confidential fields across the AI workflow, then mask, remove or restrict them according to rules agreed with your team. Access to sensitive data is limited to approved people and services, and every access decision is recorded. This is checked as part of the same testing process used for accuracy and safety. Sensitive-data handling is documented in the delivery so you can show it to auditors or customers.

You provide access to the AI system or its interface, real example interactions if available, and your domain experts' time to define what a good answer looks like. If the system is already live, we review it directly rather than needing a rebuild. No changes to the underlying model are required to begin testing. Sensitive data handling rules are agreed before any review of real interactions begins.

A first evaluation report is typically ready in 2 to 4 weeks, covering test set creation, expert-reviewed correct answers and initial scoring. Timelines depend on how many use cases are in scope and how much domain expert time is available for review. Ongoing monitoring then runs continuously once the system is live. Retesting after each change is faster since the test set already exists.