Your team just deployed an AI agent that can query databases, call APIs, and take action across systems—and nobody can answer a simple question: what would actually stop it from doing something it shouldn’t? The observability dashboard shows every call it made, but a log is not a control. By the time compliance asks for an audit trail explaining why an agent touched a customer record or escalated a request, the answer is buried in application code nobody wrote to be read by a regulator.
This whitepaper unpacks the architectural decisions standing between a promising pilot and a production deployment your compliance team will actually sign off on. Inside, you’ll find why locking into a single LLM provider is a bigger risk than it looks, what separates a framework built for governance from one where it’s bolted on, and the points in an agent’s execution flow where real control—not just monitoring—has to happen. Download it to see how enterprises are turning governance from a blocker into a foundation.