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: XenonStack
Industry: AI Governance & Compliance Technology
Location: Global
Company Size: -----
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.
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.
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.
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
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.
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.
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
Continuous Compliance Fabric: Always-on oversight eliminates compliance crunches.
AI-Aware Governance: Drift, bias, and fairness monitoring built directly into AI oversight.
AWS-Native Advantage: Direct integration with IAM, Config, Security Hub, SageMaker.
Audit Portals: Real-time evidence APIs reduce audit delays.
Extensibility: MCP/LangGraph/A2A orchestration integrates with DevOps, SecOps, FinOps.
Audit Efficiency: 50% reduction in audit preparation time.
Cost Savings: 40% reduction in compliance operational costs via automation.
AI Risk Mitigation: Continuous oversight reduced incidents of model drift/bias by 35%.
Audit Readiness: Year-round evidence availability eliminated “compliance crunch.”
Scalability: Successfully managed compliance across 100+ AWS accounts/regions.
Performance: Real-time compliance dashboards with sub-second evidence retrieval via Elasticache.
Scalability: EKS-based oversight agents scaled dynamically.
Reliability: Multi-region S3 replication ensured evidence resilience.
Security: End-to-end encryption with AWS KMS + controlled auditor access.
Integration: Embedded compliance into CI/CD pipelines for DevOps alignment.
Agent GRC has transformed compliance into a continuous process. With autonomous oversight and AWS-native integrations, we’ve eliminated last-minute audit pressure and gained real-time visibility into AI risks.
- CTO, XenonStack
Audit Fatigue: Automated evidence pipelines reduced manual effort.
Vendor Oversight: Integrated monitoring of third-party LLMs closed compliance gaps.
AI Black-Box Risks: Implemented explainability and lineage for SageMaker/Bedrock.
Define compliance KPIs early (e.g., audit readiness, AI drift thresholds).
Prioritize encryption and access control from day one.
Embed governance into CI/CD pipelines.
Use HIL workflows for sensitive AI use cases.
Expand governance for multi-cloud compliance (Azure, GCP).
Enhance AI fairness monitoring with SageMaker Clarify.
Extend evidence analytics with Amazon QuickSight dashboards.
Support edge AI compliance with Outposts/Local Zones.
Build regulatory intelligence packs for new frameworks (e.g., US AI Bill of Rights).
Agent GRC on AWS redefines compliance for the AI era. By embedding autonomous oversight, unified regulatory mapping, and audit-ready automation into AWS, enterprises gain resilience, trust, and operational efficiency. With future-focused enhancements, Agent GRC positions XenonStack as a leader in AI-powered governance and compliance.