Project introduction
TrustOps Automation is a multi-agent closed-loop operations platform for high-value operations and security teams, as well as other high-risk business scenarios such as autonomous-driving sensor-fusion failures and e-commerce payment-system incidents. It turns fragmented alerts into a traceable, replayable, auditable task chain: Agents collaborate on signal correlation, competing root-cause analysis, policy approval, reversible execution, independent verification, and post-incident review. Mission Control governs permissions, leases, recovery, evidence, and review, preventing Agents from certifying their own success.
The project has established a deterministic digital-twin baseline, an isolated closed loop, evidence sealing, and the foundation of a reinforcement-learning flywheel, including versioned event contracts, read-only collection, outcome labels, baseline evaluation, safe replay, and quality dashboards. Next, shadow mode will optimize alert, root-cause, and Skill recommendations, followed by bounded reinforcement-learning experiments under approval, rollback, and independent-verification constraints. Domain adapters can be reused for extensions such as payment recovery without forking the core architecture.
Open-source repository
Explore the open-source repository for implementation details, documentation, and progress evidence.