Agent GRC: AI-Powered Governance, Risk & Compliance on AWS

Executive Summary 

XenonStack developed Agent GRC, an AI-powered Governance, Risk, and Compliance (GRC) orchestration platform built natively on AWS. As enterprises scale AI adoption and cloud workloads, traditional compliance tools fall short with periodic, manual, and reactive processes. Agent GRC shifts compliance into a continuous, autonomous discipline. Leveraging AWS services such as IAM, Config, CloudWatch, GuardDuty, Macie, and SageMaker, the solution provides year-round audit readiness, AI risk monitoring, and unified regulatory mapping. Organizations achieved continuous compliance, reduced audit fatigue, improved risk transparency, and 40% lower compliance operational costs. 

Customer Challenge 

Customer Information 

• Customer: XenonStack 

• Industry: AI Governance & Compliance Technology 

• Location: Global 

• Company Size: ----- 

Business Challenges 

• Fragmented Regulations: Overlapping standards (SOC 2, HIPAA, GDPR, PCI-DSS, NIST, EU AI Act) created redundant compliance efforts. 

• Reactive Compliance: Teams scrambled during audits to collect CloudTrail logs, IAM mappings, and S3 evidence, leading to “compliance crunches.” 

• AI Risk Exposure: SageMaker/Bedrock workloads faced drift, bias, and explainability risks. 

• Vendor Blind Spots: Third-party SaaS/LLMs lacked oversight, creating compliance gaps. 

• Audit Fatigue: Manual evidence gathering caused errors, delays, and rising costs. 

Technical Challenges 

• Legacy GRC Systems: Not designed for AWS-native, real-time monitoring. 

• Integration Complexity: Traditional tools lacked synchronization with AWS Config, GuardDuty, and multi-account setups. 

• Scalability: Compliance pipelines couldn’t scale with multi-region deployments. 

• Evidence Management: Storing, indexing, and retrieving audit artifacts was manual. 

• AI Oversight: Monitoring fairness, lineage, and drift required GPU-enabled resources and new governance models.  

Partner Solution 

Solution Overview 

XenonStack partnered with AWS to deliver Agent GRC, embedding autonomous oversight agents within AWS environments. The solution enables: 

• Continuous Oversight: Agents monitor IAM drift, Config violations, GuardDuty findings, and SageMaker model performance. 

• Unified Regulatory Mapping: “Implement once, satisfy many” by mapping AWS Config rules to multiple frameworks. 

• AI Risk Intelligence: Continuous scoring of drift, bias, anomalies, and lineage in AI workloads. 

• Audit Automation: Evidence stored in Amazon S3 and indexed via DynamoDB/Redshift ensures year-round readiness. 

• AWS-Native Integration: Built on IAM, Config, CloudWatch, Security Hub, Macie, and SageMaker for seamless adoption.  

AWS Services Used 

• Identity & Compliance: IAM, IAM Identity Center, Config, Control Tower 

• Monitoring & Security: CloudWatch, CloudTrail, Security Hub, GuardDuty, Inspector, Macie 

• Data & Storage: S3 (evidence lake), DynamoDB/RDS (metadata), Redshift (dashboards), OpenSearch (indexing), Elasticache (low-latency) 

• AI Oversight: SageMaker, Bedrock 

• Event-Driven Orchestration: Step Functions, EventBridge, Lambda 

• Encryption & Privacy: AWS KMS for evidence encryption 

• ETL & Analytics: Glue for compliance data pipelines 

 Architecture Diagram 

• Core (Agent GRC): Oversight agents, regulatory mapping, risk intelligence, evidence automation, AI governance, orchestration (MCP/LangGraph/A2A). 

• AWS Services: IAM, Config, CloudWatch, Macie, GuardDuty, S3, DynamoDB, Redshift, Elasticache, OpenSearch, Glue. 

• External Systems: ERP/CRM platforms (SAP, Salesforce, Oracle), vendors, LLMs. 

• Dashboards & Auditor Portal: Real-time risk visibility and evidence access. 

Implementation Details 

The implementation followed Agile + DevOps principles: 

• Phase 1 – Discovery (Weeks 1–2): Defined compliance workflows, mapped frameworks, identified AWS services. 

• Phase 2 – Development (Weeks 3–8): Built oversight agents on EKS/EC2, integrated SageMaker drift monitoring, implemented evidence automation in S3/DynamoDB. 

• Phase 3 – Integration & Testing (Weeks 9–12): Connected ERP/CRM and CI/CD pipelines; tested regulatory mapping and dashboards. 

• Phase 4 – Deployment & Monitoring (Weeks 13–16): Multi-region deployment via CloudFormation; enabled auditor portals and real-time dashboards. 

Security & Compliance Considerations 

• IAM + SSO with RBAC 

• KMS encryption for evidence 

• GuardDuty, Inspector, Macie for threat detection & privacy 

• Human-in-the-loop (HIL) workflows for high-risk AI models