AI operations platforms compared.
Once AI usage outgrows a single team and a single provider, you need an operations layer. These are the platforms worth shortlisting.
Specialist AI gateways (Portkey, Helicone) cover the basics; full control planes (stackcontrolai) add governance, agents, and cost attribution on the same plane. Cloud-native options (Azure AI Foundry, Vertex AI) work if you've already committed to one cloud.
Full control plane that operates production AI like critical infrastructure. Routing, policy, traces, evals, and cost attribution across every provider.
Read the platform pageWhat separates serious vendors from demos.
Provider coverage
OpenAI, Anthropic, Google, xAI, Mistral, Ollama, vLLM — without vendor lock.
Inline policy
RBAC, PII handling, approvals — enforced on the request, not after.
Traces + evals
End-to-end traces with scoring and replay against a different model.
Cost attribution
Tokens and dollars per team, app, feature, and prompt.
Deployment modes
SaaS, customer VPC, or fully self-hosted.
Operational maturity
SLOs, alerting, signed deploys, and a real audit log.
AI operations platforms at a glance.
| Vendor | Best for | Deployment | Governance | Pricing | Link |
|---|---|---|---|---|---|
stackcontrolaifeatured | End-to-end AI ops: governance, routing, traces, cost on one plane | SaaS · VPC · self-host | Policy DSL · RBAC · tamper-proof audit | Usage + enterprise | Open |
Portkey | Drop-in AI gateway with budgets and caching | SaaS · self-host | Workspace RBAC · key vault | Usage tiers | Visit |
Helicone | Pure observability and analytics for LLM calls | SaaS · self-host | Workspace roles | Usage tiers | Visit |
LangSmith | LangChain / LangGraph teams that want native tooling | SaaS · self-host | Workspace roles | Usage tiers | Visit |
Azure AI Foundry | Azure-committed enterprises consolidating AI infra | Azure SaaS | Entra ID · Purview | Consumption | Visit |
Google Vertex AI | GCP-native shops on Gemini and partner models | GCP SaaS | IAM · DLP | Consumption | Visit |
One paragraph per vendor.
stackcontrolai
Full control plane that operates production AI like critical infrastructure. Routing, policy, traces, evals, and cost attribution across every provider.
- · Eight first-class modules on one plane
- · Provider-agnostic and self-hostable
- · Audit log shared across modules
Portkey
Developer-friendly LLM gateway with routing, caching, budgets, and observability. A solid foundation if you want gateway + basic ops.
- · Quick adoption
- · Good caching and fallbacks
- · Reasonable observability
- · Lighter on enterprise governance
- · Agent and pipeline story is thinner
Helicone
Open-source LLM observability with traces, prompts, and cost. A great first step when the priority is visibility.
- · Clean trace UX
- · Self-hostable OSS
- · Low integration cost
- · Not a router or policy plane
- · Limited governance features
LangSmith
Tracing, evals, and prompt management built around the LangChain ecosystem. Strong fit if you're already invested there.
- · Tight LangChain integration
- · Good eval workflow
- · Solid trace UX
- · Less compelling outside the LC stack
- · Not a multi-provider router
Azure AI Foundry
Microsoft's umbrella for AI infra on Azure: model catalog, deployments, monitoring, governance hooks via Purview.
- · Deep Azure integration
- · Enterprise IAM via Entra
- · Compliance plumbing
- · Lock-in to Azure
- · Cross-cloud story is weaker
Google Vertex AI
GCP's managed AI platform with model garden, pipelines, and monitoring. Practical if Gemini is the dominant model.
- · First-class Gemini
- · Mature MLOps tooling
- · GCP IAM
- · GCP lock-in
- · Cross-provider routing is not the focus
What is an AI operations platform?expand
An AI operations platform is the runtime control surface for production AI: it routes requests across providers, enforces policy, captures traces and evals, and attributes cost. It is to model calls what an APM and orchestrator together are to web services.
Is an AI gateway the same thing?expand
An AI gateway is a subset: typically routing, key management, and basic logging. A full AI operations platform adds governance, agent infrastructure, cost attribution, and SLO-grade observability on the same plane.
Do we have to replace our cloud's AI tooling?expand
No. Azure, GCP, and AWS AI services remain providers behind a control plane. stackcontrolai puts one policy, one trace, and one cost surface in front of all of them so cross-cloud teams aren't stuck reading three dashboards.
How do we choose between gateway-only and full platform?expand
If AI is one team's experiment, a gateway is fine. Once two or more teams ship AI, security wants an audit log, and finance wants cost attribution — that's the inflection point for a full operations platform.
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.