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Not long ago, AI agents were harmless. They wrote snippets of code. They answered questions. They helped individuals move a little faster. Then organizations got ambitious. Instead of personal copilots, companies started deploying shared organizational AI agents - agents embedded into HR, IT, engineering, customer support, and operations. Agents that don't just suggest, but act. Agents that touch real systems, change real configurations, and move real data: An HR agent who provisions and deprovisions access across IAM, SaaS apps, VPNs, and cloud platforms. A change management agent that approves requests, updates production configs, logs actions in ServiceNow, and updates Confluence. A support agent that pulls customer data from CRM, checks billing status, triggers backend fixes, and updates tickets automatically. These agents warrant deliberate control and oversight. They're now part of our operational infrastructure. And to make them useful, we made them powerful ...

Organizations handling various forms of sensitive data or personally identifiable information (PII) require adherence to regulatory compliance standards and frameworks. These compliance standards also apply to organizations operating in regulated sectors such as healthcare, finance, government contracting, or education. Some of these standards and frameworks include, but are not limited to: Payment Card Industry Data Security Standard (PCI DSS) General Data Protection Regulation (GDPR) Health Insurance Portability and Accountability Act (HIPAA) National Institute of Standards and Technology Special Publication framework (NIST SP 800-53) Trust Services Criteria (TSC) Cybersecurity Maturity Model Certification (CMMC) Reasons for meeting compliance requirements Below are some reasons for meeting compliance requirements: To protect businesses and organizations from cybersecurity risks, threats, and data breaches. To develop efficient organizational processes that aid in atta...