AI Platform Governance & Control
Trace model decisions, control bias, monitor usage and consumption
Too many AI projects go into production without governance: untracked decisions, uncontrolled bias, costs and consumption out of sight — and ethical and hallucination risks that no one manages. We define audits, rules, and operating models to trace AI model decisions, control algorithmic bias, and monitor usage and consumption. This is platform governance — at the organizational level — that makes AI reliable and keeps it under control.
The service in brief
- Service
- Governance and control of AI platforms: audits, rules, and operating models.
- When you need it
- AI is in production but without rules: decisions go untracked, and bias and consumption are out of control.
- R.O.C.E. phase
- Control: the third phase of the Miriade R.O.C.E. methodology (Recover · Optimize · Control · Evolve).
- Level
- Platform governance at the organizational level — not individual projects.
- Scope
- AI models, decisions, bias, usage and consumption, policies, and audits.
- Distinct from
- AI in Production Enablement (which operates a specific solution) and MirAI (the continuous managed service).
When AI runs without rules
The service fits when AI enters the processes that matter and you need to trace, control, and explain it — not just make it work.
Rules and control over the models
Model audits
Audit rules and procedures to verify how models behave, with which data, and with which results over time.
Decision tracking
We track the decisions made by models to make them explainable, verifiable, and defensible — including toward regulators.
Bias control
We identify and keep algorithmic bias under control, reducing ethical, reputational, and compliance risks.
Usage and consumption monitoring
We monitor who uses the models, for what purposes, and with what consumption, to keep usage and costs under control.
AI you can trust
AI you can trust is AI you can trace, control, and explain.
Governance is not done project by project, but at the platform level: rules, audits, and operating models that apply to every model in use — so reliability and compliance do not depend on a single team.
Success stories
Miriade insights on governance, trust, and compliance of AI systems.
AI governance with AI TRiSM
Managing the trust, risk, and security of artificial intelligence systems with a structured framework.
Learn more Case studyMeeting the challenge of the AI Act
EU Regulation 2024/1689 and Italy's Law 132/2025: how to bring AI use in your company into compliance.
Learn moreThe tools of governance
AI governance is one of the pillars of control in this area, alongside observability, security, and data governance.
Observability, DataOps & AIOps
End-to-end visibility, predictive AIOps, and data flow automation.
AI Platform Governance & Control
Audits, rules, and control over AI model decisions, bias, and consumption.
You are hereDevSecOps & DataSecOps
Shift-left security in pipelines and protection of sensitive data.
ControlData Governance & Data Quality
Data Catalog, Data Lineage, and Data Masking for reliable data.
ControlSRE & Continuous Platform Support
Continuous management of business-critical platforms based on SRE principles.
Frequently asked questions
How is it different from AI in Production Enablement?
That service brings a specific AI solution into production and keeps it there. This one governs models and platforms at the organizational level, with rules that apply to all.
Does it help with AI Act compliance?
Yes. Audits, decision tracking, and model control are the foundation for meeting regulatory obligations on the use of AI.
Does it also control AI costs?
It monitors model usage and consumption. Fine-grained cost optimization for large language models (LLMs) and agents is the AI Context & LLM Optimization service.
Is it only for organizations with many models?
No. It is useful as soon as AI enters processes that matter, even with only a few critical models to trace and control.
What about bias and hallucinations?
They are kept under control with audits, decision tracking, and operating rules, reducing ethical and reputational risks.
Is it an assessment or a continuous managed service?
It starts with an assessment and leads to continuous governance. Monthly operational management of AI systems is the MirAI service.
Want AI that is traceable and under control?
Tell us which models and use cases you have in your organization and which risks concern you. We start with a governance assessment and define audits, rules, and controls for your models.
Traceable AI, under control
Tell us which models and use cases you have in your organization and which risks concern you. We start with an assessment and define audits, rules, and controls for your models.
We use the data you submit only to contact you about this request.
