evaluagent Introduces Context Engine for Smarter QA

evaluagent has launched Context Engine, a feature designed to improve AI-driven quality assurance in contact centres by assessing whether agents provide correct information, not just well-delivered responses.

“We built AutoQA to give contact centres objective, scalable quality scores,” said Matt Jones, Head of Product of evaluagent. “It gave teams more insight than they’d ever had, but the missing piece was whether agents were giving the right answer. Context Engine solves that.”

The system evaluates conversations against each organisation’s own policies, knowledge base, and business rules, and also builds on existing automated QA methods, which already measure factors such as tone, compliance, and process adherence, by addressing gaps in factual accuracy.

Context Engine uses configurable company information and uploaded documentation to identify when agent responses conflict with internal guidelines.

Elizabeth Gunn, Product Manager at evaluagent, added: “This is all about giving customers the ability to provide AI scoring context.

The quality of an evaluation depends entirely on the knowledge behind it – Context Engine provides that, meaning AI scoring gets even closer to that of your best QA evaluators. That frees up the human team for more valuable activity, like deeper reporting and agent coaching.”

Early testing showed improved alignment between AI and human evaluations, with organisations reporting clearer and more accurate assessments.

The feature is intended for environments where accuracy is critical, including regulated industries and complex customer interactions.

For more information about evaluagent - visit the evaluagent Website