We built the quality checks that keep an AI assistant trustworthy over time
An AI assistant already in daily use risked losing quality with every update, with no way to catch it.
- Sector
- Telecommunications
- Engagement
- AI
- Stack
- Evaluation · Monitoring · LLMOps
The challenge
The client already had a helpful AI assistant in daily use. The real risk was elsewhere: every time it was improved, its quality could quietly slip without anyone noticing — a smoother answer isn't always a better one.
The process
We put in place a system that automatically checks the assistant's quality with every new version, using a set of questions that reflect how people really use it. An update only goes live if it holds — or improves — the measured quality. A dashboard lets teams keep an eye on reliability at all times, including after launch.
What we shipped
- An automatic quality check on every new version
- A clear go / no-go before anything reaches production
- A monitoring dashboard the business team can actually read
- Early detection of quality drops before they reach users
The impact
- No more “it worked last week” — quality stayed under control
- Improvements approved on evidence, not on impression
- Issues caught before users, not after
- Lasting confidence in the tool, for teams and leadership alike
More work
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