Scaling mock inspections through agentic AI

To move beyond reactive audit preparation, Virtusa co-developed a human-in-the-loop agentic AI framework designed to simulate end-to-end regulatory site inspections. The platform used 14 specialized AI agents to automate validation workflows while keeping human auditors at the center of review and remediation.

Some agents reviewed clinical trial documentation to verify investigator credentials, staff training completion, clinical visit records, and protocol adherence. Others handled investigational product reconciliation and risk assessment by cross-referencing protocol requirements against storage conditions, destruction records, accountability logs, and other relevant data.

The human-agent collaboration operated across three layers:

Autonomous evidence mining: AI agents continuously cross-referenced clinical documentation, training records, and operational logs to identify gaps and anomalies.
Intelligent escalation and contextual delivery: Rather than presenting raw findings, the system synthesized results, categorized risks by priority (low, medium, high), and recommended remediation paths.
Human-guided decision-making: Human auditors reviewed AI-generated reports, validated deviations, and executed corrective actions while the framework refined its accuracy through feedback loops.

By automating mock inspections and audit summarization, the platform reduced readiness timelines from weeks to days and improved visibility across site operations.

2–3 days

14

70%

80%

60%

50%

Services

Industries

Insights

Careers

About