Our Science

Architecture & Training

Evidence Tracer Agent uses a hybrid architecture combining deterministic rule-based control mapping with machine learning enhancement. The core engine applies direct mappings from AWS CloudTrail events, IAM policies, S3 configurations, and Config rules to specific SOC 2 controls using established compliance frameworks. ML models provide risk scoring, anomaly detection, and pattern recognition for configuration drift and evidence freshness optimization. This approach ensures 100% explainable compliance mapping while leveraging AI for intelligent prioritization and gap analysis.

The ML enhancement layer is trained on 10,000+ anonymized AWS audit cycles from SaaS and Fintech companies, using transformer-based event sequence analysis and graph neural networks to understand AWS resource relationships and compliance dependencies.

Technical Process

1. Real-Time Stream Processing - Parallel ingestion from CloudTrail API, IAM Policy Simulator, S3 Bucket Analytics, and Config API using async event handlers

2. Hybrid Evidence Classification - Rule-based control mapping with ML-powered risk scoring and compliance relevance analysis achieving 94% accuracy

3. Deterministic Control Mapping - Direct mappings to SOC 2 controls using established compliance frameworks with full audit traceability

4. ML-Enhanced Gap Detection - Identifies missing evidence, policy violations, and configuration drift using temporal analysis, compliance baselines, and anomaly detection

5. Intelligent Report Generation - Automated compilation of audit-ready documentation with evidence lineage, gap remediation recommendations, and ML-powered priority scoring

Data Security & Privacy

All processing occurs in real-time with zero data persistence. User AWS credentials use read-only IAM roles with least-privilege access. Evidence data is processed in-memory and immediately discarded post-analysis. No customer data, configurations, or evidence items are stored, logged, or transmitted to third parties. All communications use TLS 1.3 encryption with certificate pinning.

Performance Metrics

- Processing throughput: 1,000+ evidence items in minutes

- AWS API call optimization: 85% reduction vs. manual collection

- Control mapping accuracy: 94% precision across 8 SOC 2 domains

- Memory efficiency: <2GB peak usage for enterprise-scale AWS environments

- Explainability: 100% traceable rule-based mappings with ML confidence scores