Prompt injection, leakage, and jailbreaking are mitigated through secure prompt design, isolation from user input, and instructional redundancy. Bias mitigation, refusal scaffolds, and profanity filters ensure agents don’t provide unauthorized medical, legal or financial advice, stray from scope, or generate offensive responses.

Calls are monitored in real-time for anomalies like forbidden topics, hallucinated actions, excessive response lengths, and signs of bias. Severity-based controls allow us to flag, intervene, or terminate sessions as needed, to prevent operational drift, unsafe behavior, or escalation of risky patterns.

Agents run in sandboxed containers isolated from core databases. They receive only the minimum data needed to perform the workflow for a single patient. This minimizes exposure, enforces task limits, and prevents data leakage—aligned with the principle of least privilege and zero trust access.

Flagged calls and random samples are regularly reviewed by authorized QA teams. In cases where out-of-scope queries arise or customers opt in, agents escalate to human staff. This provides a final checkpoint to ensure accuracy, maintain trust, and handle sensitive conversations appropriately.

Insights from red teaming, real-world usage, and stakeholder feedback—including clinicians, patients, and ops teams—are continuously fed back to improve prompts, detection rules, and infrastructure. This helps patch vulnerabilities and adapt quickly to emerging threats.