The Platform · Moring AICP
A single control plane for enterprise AI.
One place to build, deploy, manage, and govern.
Moring AICP is the engine enterprise teams use to build a single control plane, where AI workflows are built, deployed, managed, and governed in one place.
Architecture
One control plane. Your existing cloud underneath.
The AI Control Plane deploys on top of the cloud infrastructure you already operate. We add the governance, policy enforcement, and agent controls your team needs without disrupting what already works - Kubernetes, observability, CI/CD, IaC, your existing security and compliance posture all stay.
Control plane capabilities · the building blocks
The building blocks of the control plane.
Grouped by the role each one plays. Authentication & Authorization is the policy layer everything else runs on. The rest are where that policy is enforced, how AI gets built and approved, and where agents run and stay under control.
Policy layer
Authentication & Authorization
One policy model that decides what every AI workflow is allowed to do — its models, tools, skills, sandbox, network, and retrieval APIs. Connects to your IDP and adds a policy layer with OPA or Cedar.
What agents use
AI Gateway
The controlled way agents and developers reach AI models — coding assistants and production agents alike. Use the built-in gateway or bring your own; model access follows the same policies as everything else.
What agents use
MCP Platform
Registry, runtime, and gateway to register, run, and control the MCP servers agents use to reach tools and data (built on ToolHive). Federated: each business unit runs its own, all governed from one registry.
What agents use
Managed Skills Registry
One registry of the AI skills approved for the enterprise, with a pipeline that scans them for vulnerabilities. At runtime, an agent downloads only the skills its policy permits.
Build & approve
Pattern Library · Blueprints
Pre-approved, ready-to-use patterns with working reference implementations — router-and-specialist, human approval, MCP tools, skills — with threat modeling already signed off. Build on one and reach production without a new security review.
Build & approve
Governance Workflow Engine
Build the approval and onboarding workflows that govern AI. Onboarding provisions the right model, tool, and skill access, sets who can invoke a workflow, and routes it through required security & governance sign-offs.
Build & approve
Secure Human-in-the-Loop
Ready-made modules that add safe human steps inside a running workflow. Reviewers get short-lived, just-in-time access — granted only when needed, and expiring afterward.
Build & approve
SME Tooling
Tools that let subject-matter experts build, test, and give targeted feedback on agents — on top of the agent’s real traces. Expert feedback is the missing piece that makes agents reliable.
Run & control
Agent Runtime
The production environment where agents actually run — wired to the MCP gateway, the sandboxes agents run in, and the retrieval APIs they call — keeping each agent inside the boundaries its policy sets.
Run & control
Agent Registry
A single place that lists every agent in the enterprise and lets teams act on them — including applying a kill switch to a set of agents directly from the registry.
Run & control
Cost Controls
Budgets and chargeback. Every workflow and agent is metered by tokens and cost; budgets are enforced, not just reported, with loop and step caps so a stuck agent can’t run up the bill — then charged back to the team that owns it.
Deploy on your cloud
Your infrastructure. Our AI layer. Full control.
The platform runs on the cloud infrastructure you already operate — AWS, Azure, GCP, or on-premises. Your data never leaves your environment. Your keys, your perimeter, your audit trail.
Multi-cloud and hybrid deployment supported out of the box.
Zero data exfiltration - everything stays inside your VPC.
Kubernetes-native with Helm charts and Terraform modules.
SOC 2, ISO 27001, HIPAA compliant infrastructure patterns.
Composable by design
Start with one component. Expand as you grow.
No big-bang deployment. Each module works independently and integrates seamlessly with your existing observability, CI/CD, and security tooling.
Incremental adoption - start small, scale fast.
Works with your stack - your existing observability and CI/CD tools.
API-first design with comprehensive SDKs.
Each component production-ready on its own.
Built for production
Enterprise AI needs the same rigor as enterprise software.
Reliability, security, and observability baked in from day one — not as an afterthought. These are the numbers the platform operates against, every day, across every customer.
99.9% uptime SLA with automated failover.
Real-time cost tracking and budget controls.
Full audit trails for compliance and governance.
Automated evaluation before every deployment.
One control plane · powers every solution
The same control plane ships AI-DLC, AI Ops, and your custom agents.
Whichever solution you start with, you're standing on the same infrastructure. Year-two business agents amortize on the same gateway, the same observability, the same security layer. Build once, deploy many.
AI-DLC
AI-DLC for engineering.
Governed agentic SDLC. Per-PR cost attribution. Failure drill. 5-engineer case study. Same platform components, scoped to the engineering use case.
AI Ops
AI Ops for operations.
Event correlation. Topology-aware RCA. Predictive ops. Automated remediation. Same platform components, applied to operational intelligence.
Future suites
Finance·Customer ops·more.
Year-two persona suites for Finance and CS & Service ship on the same platform. The substrate amortizes. The second agent costs less than the first.
How adoption works · governance first
Governance goes on before your developers arrive.
A typical customer moves through three stages. Our forward-deployed engineers build the control plane and lay down governed patterns first — so by the time developers arrive, the rules are already in place.
Stage 01 · ~3–5 weeks
Build the control plane.
Our forward-deployed engineers use the AICP engine to build your control plane, tuned to your environment. You end this stage with a working control plane.
Stage 02 · governed patterns
Deploy reference implementations.
Before any developer is let in, we deploy 10–20 common workflow patterns tailored to you, each with a working reference implementation. Your governance team sets the first policies on these.
Stage 03 · developers build
Ship to production, fast.
Your developers build their own workflows on top, following concrete references. As long as a workflow fits a pattern, governance is already on by default — so they reach production quickly.
What makes us different
Governance goes on before developers arrive, not after. A developer’s first day already happens inside a governed environment - so governance isn’t a gate they hit later; it’s the ground they start on.
Common questions
Questions teams ask before they build.
Ready to build on Moring AI?
See how the platform ccelerates your AI initiatives.
A 30-minute AI Discovery workshop with Rajarajan gets you a baseline metric, an architecture sketch against your stack, and a yes/no on outcome pricing — before anyone signs anything.