AI governance software, compared.
AI governance is no longer a quarterly review — it ships inline on every model call. These are the platforms enterprise security and risk teams are actually evaluating.
Most AI governance tools fall into two camps: catalog-and-policy GRC platforms (Credo, Holistic, IBM) and inline runtime control planes (stackcontrolai). If you need policy enforced on every prompt — not just a register of models — pick a runtime tool.
Enforces policy in the request path: PII redaction, prompt blocks, approval chains, and a tamper-proof audit log. Ships pre-mapped to SOC 2, ISO 27001, and the EU AI Act.
Read the platform pageWhat separates serious vendors from demos.
Inline enforcement
Does policy actually block a call, or only flag it after the fact?
Audit completeness
Tamper-evident log of actor, model, prompt, output, and policy decision.
RBAC + ABAC
Per-model, per-dataset, per-tool access with environment scoping.
Framework mappings
SOC 2, ISO 27001, EU AI Act, NIST AI RMF — and evidence collected automatically.
Deployment modes
SaaS, customer VPC, or self-hosted for regulated regions.
Integration with model traffic
Sits in the request path vs. observes from outside.
AI governance software at a glance.
| Vendor | Best for | Deployment | Governance | Pricing | Link |
|---|---|---|---|---|---|
stackcontrolaifeatured | Inline policy + audit on every model call, across providers | SaaS · VPC · self-host | Policy DSL · RBAC · tamper-proof audit | Usage + enterprise | Open |
Credo AI | GRC teams managing AI model registries and risk policies | SaaS | Policy library · model registry | Enterprise | Visit |
Holistic AI | Bias and fairness assessments across model portfolios | SaaS | Assessments · audits | Enterprise | Visit |
IBM watsonx.governance | IBM-aligned shops with existing governance estate | SaaS · on-prem | Factsheets · lifecycle | Enterprise | Visit |
Lakera Guard | Prompt-injection and content-safety inline guardrails | API · SaaS | Real-time guardrails | Usage | Visit |
Microsoft Purview AI Hub | Microsoft 365 / Copilot estates | SaaS (Microsoft 365) | DLP · compliance | Bundled · enterprise | Visit |
One paragraph per vendor.
stackcontrolai
Enforces policy in the request path: PII redaction, prompt blocks, approval chains, and a tamper-proof audit log. Ships pre-mapped to SOC 2, ISO 27001, and the EU AI Act.
- · Inline enforcement, not just risk register
- · Same plane as routing, traces, and cost
- · Approval chains wired to audit
Credo AI
Governance platform focused on model intake, risk scoring, and policy attestation. Strong for risk and compliance teams running formal review processes.
- · Mature policy library
- · Good for model intake workflows
- · Strong GRC orientation
- · Observes rather than enforces inline
- · Limited runtime control over live traffic
Holistic AI
AI risk platform with a focus on bias, fairness, and compliance assessments. Useful where regulatory reporting is the binding constraint.
- · Strong assessment toolkit
- · Regulatory templates
- · Audit-friendly outputs
- · Assessment-led, not runtime control
- · Not designed to sit in the request path
IBM watsonx.governance
Lifecycle governance across model development, deployment, and monitoring. Natural fit if you already run IBM data and AI stacks.
- · Deep lifecycle features
- · On-prem option
- · IBM ecosystem alignment
- · Heavy footprint
- · Best ROI inside the IBM stack
Lakera Guard
Specialized runtime guardrails focused on prompt injection, data exfiltration, and toxic content. Often deployed alongside a broader governance platform.
- · Strong attack-pattern coverage
- · Low-latency runtime checks
- · Easy to drop in
- · Not a full governance platform on its own
- · No audit/RBAC across the stack
Microsoft Purview AI Hub
Extends Purview compliance controls to AI usage inside Microsoft 365 and Copilot. Strong if Copilot is the dominant AI surface.
- · Tight Microsoft 365 integration
- · Familiar DLP model
- · Existing compliance plumbing
- · Limited reach outside Microsoft stack
- · Not vendor-agnostic for model traffic
What does AI governance software actually do?expand
At minimum: keep a register of models in use, document their risk, and produce evidence for auditors. The newer generation goes further — enforcing policy on every prompt and call in real time, and capturing a tamper-evident audit log of every decision.
Is a model registry enough for the EU AI Act?expand
Not for high-risk systems. The EU AI Act requires risk management, data governance, logging, transparency, human oversight, and accuracy/robustness controls — most of which are runtime obligations, not documentation. A registry helps; it does not satisfy the obligations on its own.
Where does Lakera or a guardrail tool fit versus stackcontrolai?expand
Guardrail tools like Lakera focus on attack-pattern detection on individual prompts. stackcontrolai is a full control plane: it can call Lakera as one of its policy checks, but also owns RBAC, audit, multi-model routing, and cost. They are complementary.
How do we adopt without a big-bang rollout?expand
Start with one team or one model. Put stackcontrolai in front of their traffic in observe-only mode, then turn on policy enforcement once the signal is trusted. Expansion is per route, not per quarter.
Skip the demo loop. Run it on your stack.
The live console mirrors what stackcontrolai does in production — governance, routing, traces, and cost on one plane.