AI Answer Accuracy Assessment for Contact Centers and AI Assistants

Companies are turning on AI assistants - in contact centers (such as Amazon Q in Connect), customer self-service and internal help desks - that answer questions from company documents: insurance policies, banking product terms, health plan benefits, HR policies, product manuals and knowledge articles. These assistants can sound confident and cite a document while stating the wrong amount, mixing up two products or plans, dropping a condition that changes the answer, or answering questions the documents don't cover. Few teams can measure how often that happens.

Tech Arch Inc runs an independent accuracy assessment on your setup. We build a test set of realistic customer questions from your own documents, where every expected answer is backed by verbatim quotes and page numbers checked in code against the source. We run the questions against your AI assistant and grade every response.

You receive a scorecard by document and topic showing correct answers, answers missing an important condition, wrong answers, answers taken from the wrong product or plan, and made-up answers to questions your documents don't cover. Each failure links to the exact page and text in your documents.

We then recommend concrete fixes - for example scoping answers to the right product or plan, restructuring hard-to-read tables into plain-language knowledge content, and tightening the assistant's answer rules - and re-test to show the improvement. In our own benchmark on 19 real health plan documents, these fixes cut wrong answers by about 78%.

The assessment works with assistants built on AWS services such as Amazon Q in Connect and Amazon Bedrock knowledge bases, runs in your AWS account, and your documents and results stay with you. Engagements start with a kickoff call and end with a results walkthrough for your operations, quality and compliance teams.