Managing compliance audits often feels like a digital scavenger hunt, requiring teams to manually capture hundreds of screenshots across disparate systems like GitHub and AWS consoles. This labor-intensive process is not only prone to human error but also difficult to replicate during subsequent audit cycles. AWS has addressed this friction by designing an intelligent system that pairs browser automation with large language models to streamline evidence gathering.

At the heart of this solution is a browser extension powered by Amazon Bedrock and the Nova 2 Lite model. The system functions as an AI agent capable of three distinct modes: designing workflows from text documents, executing automated navigation steps, and analyzing captured visuals to generate final reports. By using natural language processing to convert compliance requirements into executable scripts, the tool removes the technical barrier typically associated with browser automation.

Security remains a primary focus, with the architecture utilizing identity management and scoped permissions to ensure least-privilege access. The extension organizes all captured evidence within a structured storage hierarchy, providing a clear audit trail for regulators. This approach demonstrates how agentic AI can handle the "last mile" of enterprise workflows by interacting directly with web interfaces, even when traditional APIs are unavailable or impractical to implement.

Managing compliance audits often feels like a digital scavenger hunt, requiring teams to manually capture hundreds of screenshots across disparate systems like GitHub and AWS consoles. This labor-intensive process is not only prone to human error but also difficult to replicate during subsequent audit cycles. AWS has addressed this friction by designing an intelligent system that pairs browser automation with large language models to streamline evidence gathering.

At the heart of this solution is a browser extension powered by Amazon Bedrock and the Nova 2 Lite model. The system functions as an AI agent capable of three distinct modes: designing workflows from text documents, executing automated navigation steps, and analyzing captured visuals to generate final reports. By using natural language processing to convert compliance requirements into executable scripts, the tool removes the technical barrier typically associated with browser automation.

Security remains a primary focus, with the architecture utilizing identity management and scoped permissions to ensure least-privilege access. The extension organizes all captured evidence within a structured storage hierarchy, providing a clear audit trail for regulators. This approach demonstrates how agentic AI can handle the "last mile" of enterprise workflows by interacting directly with web interfaces, even when traditional APIs are unavailable or impractical to implement.