Deploying an AI agent in a live business environment is not an easy feat, but it is easier than what comes next. Getting it to reliably serve tens of thousands of employees across HR, IT, Finance, and Legal? That’s where most organizations hit a wall.
One of our customers, a multinational technology company, discovered this firsthand. Their internal conversational AI agent saw rapid adoption. But as reliance grew, so did the stakes. A wrong answer about a legal policy or financial procedure can have material business consequences, from compliance violations to operational disruption to employees acting on inaccurate guidance.
To solve this, the company turned to Flexor’s AI Context Engine (ACE), which unifies and contextualizes fragmented unstructured data, including emails, contracts, PDFs, and internal documents, turning it into AI-ready data. In this case, Flexor was used to analyze agent outputs to ensure that they are actually accurate, consistent, complete and trustworthy in the company’s specific business and data context, and wherever gaps were found, additional data could be brought in to increase accuracy and trust.
The result: continuous visibility into knowledge gaps, hallucinations, and policy misalignments, leading to the right data being added to the process, resulting in improved agent performance, all without disrupting existing infrastructure.
