Play 60
Responsible AI Dashboard
High✅ Ready
Enterprise RAI governance with fairness metrics and EU AI Act compliance.
Enterprise responsible AI governance platform tracking model fairness metrics, bias detection across demographics, and transparency reports. Features automated explanation generation, content safety monitoring, and EU AI Act compliance tracking. Built on Azure ML for model evaluation, Azure Monitor for real-time safety signals, and Static Web Apps dashboard for executive visibility.
Architecture Pattern
Observability dashboard: ML-powered fairness evaluation, compliance automation
Azure Services
Azure OpenAIAzure Machine LearningAzure MonitorCosmos DBStatic Web Apps
DevKit (.github Agentic OS)
- agent.md — root orchestrator with builder→reviewer→tuner handoffs
- 3 agents — RAI Dashboard Builder (gpt-4o), Reviewer (gpt-4o-mini), Tuner (gpt-4o-mini)
- 3 skills — deploy (258 lines), evaluate (117 lines), tune (194 lines)
- 4 prompts — /deploy, /test, /review, /evaluate with agent routing
- .vscode/mcp.json — FrootAI MCP with OpenAI + App Insights inputs + envFile
TuneKit (AI Config)
- config/openai.json — explanation generation, report summarization
- config/guardrails.json — fairness thresholds, safety baselines
- evaluation/eval.py — Fairness disparity <5%, Safety incident rate 0%
Tuning Parameters
Fairness disparity thresholdBias detection granularitySafety incident alert levelReport generation frequencyCompliance framework selection
Estimated Cost
Dev/Test
$60–100/mo
Production
$1.5K–4K/mo