NodeNova - AI Governance & Operations | Production Reliability

AI GOVERNANCE SERVICES

Comprehensive governance frameworks for production AI systems in regulated industries.

Model Governance: Version control for models, prompts, and configurations. Deployment approval workflows with stakeholder sign-off. A/B testing and canary deployment frameworks. Rollback procedures with automated triggers on quality regression.
Bias Monitoring: Demographic fairness testing across protected characteristics. Output distribution monitoring for drift detection. Automated alerting on bias threshold violations. Remediation workflows with documented actions.
Decision Audit Trails: Immutable logging of model inputs, outputs, and reasoning stored within your infrastructure. Full traceability for regulatory inquiries with complete data sovereignty. Tamper-evident storage with cryptographic verification. Configurable retention policies aligned to compliance requirements.
Incident Response: AI-specific incident response procedures. Escalation paths with clear ownership. Post-incident analysis and documentation. Runbook development for common failure modes.
Operational Excellence: SLO definition and enforcement for AI systems. Capacity planning and autoscaling configuration. Cost monitoring and optimization. Performance dashboards with executive reporting.

OUR GOVERNANCE APPROACH

1. Framework Assessment

Gap analysis against regulatory requirements and industry best practices. Risk assessment for AI-specific failure modes. Stakeholder mapping and accountability assignment. Policy and procedure requirements definition.

2. Implementation

Governance tooling deployment and configuration. Policy development and documentation. Training and change management. Integration with existing compliance and risk management systems.

3. Continuous Improvement

Ongoing monitoring and alerting. Regular governance reviews and updates. Incident analysis and procedure refinement. Regulatory change tracking and adaptation.

AI GOVERNANCE ARCHITECTURE

Integrated governance system deployed within your infrastructure for complete control and auditability.

        %%{init: {
            "theme": "base",
            "themeVariables": {
            "background": "#000000",
            "primaryColor": "#00d4ff",
            "primaryTextColor": "#ffffff",
            "primaryBorderColor": "#00a8cc",
            "lineColor": "#00d4ff",
            "secondaryColor": "#1a1a1a",
            "tertiaryColor": "#2a2a2a",
            "textColor": "#ededed",
            "mainBkg": "#000000",
            "secondBkg": "#1a1a1a",
            "border1": "#27272a",
            "border2": "#3f3f46"
            }
        }}%%
        flowchart TB
            subgraph GovernanceSystem["AI Governance System"]
                subgraph Registry["Model Registry"]
                    MLflow[MLflow
Version Control]
                    Artifacts[Model Artifacts
& Signatures]
                end

                subgraph Policy["Policy Engine"]
                    OPA[Open Policy Agent]
                    Checks[Pre-deployment
Compliance Checks]
                end

                subgraph Monitoring["Observability"]
                    Prom[Prometheus Metrics]
                    Grafana[Grafana Dashboards]
                    Alerts[PagerDuty Alerts]
                end

                subgraph Audit["Audit & Compliance"]
                    Logs[Immutable Audit Logs]
                    Trace[Decision Traceability]
                    Reports[Compliance Reports]
                end
            end

            subgraph Workflow["Deployment Workflow"]
                Dev[Model Development] --> Validate[Validation Pipeline]
                Validate --> Policy
                Policy -->|Approved| Deploy[Production Deploy]
                Policy -->|Rejected| Dev
            end

            Deploy --> Registry
            Registry --> Monitoring
            Monitoring --> Audit
            Audit -->|Regulatory Inquiry| Reports

Governance Capabilities

Model Registry & Version Control

Enterprise-grade model registry with MLflow integration for metadata tracking, artifact storage, and experiment lineage. Git-based versioning for models, configurations, and datasets. Immutable deployment history with cryptographic signatures. Automated model validation pipelines ensuring production readiness.

Policy as Code Enforcement

OPA (Open Policy Agent) integration for declarative policy enforcement. Automated pre-deployment compliance checks across security, fairness, and performance requirements. GitOps workflows for policy versioning and approval processes. Custom policy development for industry-specific regulatory requirements with automated testing.

Real-time Monitoring & Observability

Prometheus/Grafana stack for metrics collection and visualization. Custom dashboards for model performance, bias metrics, and system health. Automated alerting with PagerDuty integration for SLO violations. Distributed tracing with Jaeger for end-to-end request observability. Data quality monitoring with Great Expectations integration.

GOVERNANCE OUTCOMES

Structured governance that moves AI systems from pilot to production with confidence.

Risk Reduction: Proactive governance catches compliance issues before they reach production. Automated monitoring detects bias and performance drift early, enabling intervention before operational impact.
Operational Efficiency: Standardized incident response procedures reduce mean-time-to-resolution. Canary releases and automated rollback capabilities minimize deployment risk and downtime.
Regulatory Confidence: Complete audit trails provide full traceability for regulatory inquiries. Pre-built compliance documentation streamlines audit preparation across FCA, NHS, and EU AI Act requirements.
Cost Optimization: Performance monitoring enables resource right-sizing and infrastructure optimization. Early detection of model degradation prevents costly system failures and rework.
Stakeholder Trust: Transparent decision-making processes build confidence across executive, compliance, and technical teams. Clear accountability frameworks ensure ownership during incidents.
Production Readiness: Governance frameworks designed for self-hosted deployments scale with your AI adoption while maintaining compliance and data sovereignty requirements.

Regulatory Alignment

Governance frameworks aligned to emerging AI regulations and industry standards:

EU AI Act

Risk classification and documentation requirements. High-risk system compliance including human oversight, transparency, and accuracy. Conformity assessment preparation. Technical documentation and record-keeping.

UK AI Governance

Alignment with UK AI principles: safety, transparency, fairness, accountability, and contestability. Cyber Essentials certification support for public sector contracts. FCA AI governance expectations for financial services. NHS AI governance for healthcare applications.

ISO 42001

AI management system framework alignment. Risk management for AI systems. Governance structure and accountability. Continuous improvement and performance evaluation.

Schedule a call or send us a message

Send us a message or schedule a call