For many organizations, Governance, Risk, and Compliance (GRC) information lives in static documents and sprawling spreadsheets – valuable, but difficult to quickly translate into practical business decisions. Think lengthy policy manuals, audit reports buried in shared drives, and disparate evidence scattered across various systems. What if, instead of sifting through this complexity, you could ask your GRC data a direct question and receive a clear, data-backed answer? We’re building that reality with an AI system deeply contextualized by all our GRC content – risks, policies, controls, standards, evidence (like DR test results, vulnerability scan reports, and audit findings), and even regulatory citations. This isn't just about knowing we have a control; it’s about knowing if it works consistently under real-world conditions, and having demonstrable proof.
Consider this scenario: A lawyer in our legal department is reviewing a new service level agreement (SLA) with a key client. The client is demanding a more aggressive SLA, proposing a significantly shorter Recovery Time Objective (RTO) of 4 hours and a Recovery Point Objective (RPO) of 1 hour – a substantial decrease from our standard 8-hour RTO/4-hour RPO. Instead of initiating a lengthy investigation involving the IT disaster recovery team, security, and compliance, the lawyer directly queries our AI system through a simple chat interface: “Can we reliably commit to an RTO of 4 hours and an RPO of 1 hour for the ‘Project Phoenix’ application?” The AI understands the intent, instantly scans relevant policies related to data protection and business continuity, identifies the specific disaster recovery controls applicable to Project Phoenix (including backups, replication, and failover procedures), and critically, analyzes evidence from the last six DR test runs. The system then provides a clear, detailed answer, supported by data: “Based on the last six DR test runs, the average RTO achieved for Project Phoenix was 3.5 hours, with a 1-hour RPO consistently met. However, one test, conducted on March 15th, exceeded 4 hours due to a configuration issue with the database failover process. Remediation steps have been documented in incident #23456 and verified in a subsequent test. We recommend reviewing the incident report and ensuring the configuration is monitored continuously before contractual commitment.” The AI also provides links to the DR test reports, the incident report, and relevant policy documentation.
This isn’t just about faster access to information; it’s about actionable insight and significantly reduced risk. Our AI empowers informed decision-making by connecting GRC data to critical business needs. By providing quick, accurate answers, backed by demonstrable evidence, we’re breaking down the barriers between GRC specialists and the rest of the organization. Suddenly, anyone – lawyer, salesperson, or engineer – can directly query GRC data and understand the implications of their actions, fostering a culture of proactive compliance and responsible risk management. This democratization of GRC information not only streamlines processes but also allows us to confidently negotiate contracts, respond to RFPs, and ultimately, build a more resilient and trustworthy organization.