Deploy agent infrastructure
your teams build on.
Platform teams make enterprise AI real by giving every team a layer to build on. Lyzr is the control plane, pipeline, and governance for a managed agent estate.
AWS Bedrock, Azure AI Foundry, or GCP Vertex, stays exactly where it is.
LangChain, CrewAI, or custom SDKs, no migration and no rebuild.
Registry, CI/CD, observability, and governance, one layer across everything teams build.
Responsible AI, audit trail, RBAC, and data sovereignty, enforced from day one.
IT and platform teams at these organizations deploy on Lyzr
Build the layer every team
builds safely on.
Teams can build agents. Business units can experiment. But until there is a platform layer, registry, CI/CD, observability, governance, none of it is defensible at enterprise scale. That is what platform teams build, and Lyzr is the infrastructure that makes it possible without starting from scratch.
No central registry of what is running
Teams build agents independently. IT cannot see what is deployed, who owns it, or what it can access. Shadow AI is invisible until it causes a problem.
Every agent registered: owner, version, scope
No agent runs without a registry entry. Named owner, version, framework, cloud, and access scope. IT sees everything, and shadow AI becomes impossible.
No deployment pipeline for agents
Agents are pushed directly to production. No staging, no evaluation gate, no version tracking. Rollback means debugging under pressure with no trail.
Git-native CI/CD for every deployment
Every deployment tracked to the commit. Staging, eval gate, approval, production. Rollback in one command, the same pipeline discipline as your software estate.
Observability is fragmented or missing
Different frameworks, different clouds, different monitoring tools, or none at all. IT cannot answer basic questions about what agents cost or how they perform.
One observability layer across every framework
Latency, cost, hallucination scores, and policy compliance in one dashboard, regardless of framework or cloud. Live Nation governs OpenAI, Anthropic, and Databricks Genie from one plane.
Data governance is per-team and inconsistent
Every team handles credentials, access scopes, and data handling differently. The platform has no consistent policy enforcement across all agents.
Platform-wide governance, applied consistently
RBAC, RAI policies, PII masking, and data sovereignty, configured once and enforced everywhere. Every team builds on a governed foundation, with zero per-agent configuration.
What platform teams have
already deployed in production.
These are the platform capabilities IT teams have deployed on Lyzr, pulled from real engagement notes across regulated and enterprise environments.
Agent Registry and Control Plane
The foundation of every enterprise AI estate: a registry that knows every agent running in your environment, what it owns, and which version is live. Connected to CI/CD, observability, and governance. Nordstrom deployed it across 70 agents on two frameworks inside their AWS VPC; Live Nation across three LLM vendors at once.
Enterprise Security and Sovereignty
VPC deployment, zero-data-egress, RBAC at agent and data level, and SOC 2 Type II infrastructure, applied platform-wide rather than configured per team. The Wiss & Company IT Director cleared the full security review in one session. Kaigentic built their entire three-layer platform on it for air-gapped Japanese enterprise environments.
One governed platform. Every framework.
Enterprise AI platforms
built on Lyzr. In production.
IT and platform teams that deployed Lyzr: what the infrastructure requirement was, how it deployed, and where it landed.
Words from the teams that built it right.
The infrastructure decision that
every downstream team inherits.
Platform teams that make the right infrastructure decision early save every downstream team from making the wrong one. The people who spot this gap, before a dozen teams deploy a dozen governance approaches, determine how defensible the AI estate turns out to be.
The best platform conversations start with someone in IT who has already seen the problem forming, fragmented frameworks, no registry, no deployment pipeline, and wants to solve it before the CIO has to ask why nobody built the foundation.
CTO / VP Engineering
The platform infrastructure decision is theirs. They need to see the architecture, the deployment model, and the no-rebuild story directly.
EssentialCISO / Information Security
VPC deployment, zero-data-egress, RBAC, SOC 2, they will have the checklist. Come to this conversation with them, not after them.
EssentialHead of AI / Principal Architect
They own the architecture that sits above the infrastructure. The control plane, CI/CD, and observability layers need to fit their roadmap, not replace it.
EssentialA team already building agents
The teams who will use the platform surface the real requirements. One early conversation with them changes what you ask for in the evaluation.
RecommendedWhat to take into
the platform decision.
The resources IT and platform teams use to evaluate the architecture, run security reviews, and brief their leadership before the infrastructure decision is made.
One infrastructure decision.
Every team builds from it.
Bring your current stack and your infrastructure requirements. We will walk through what the control plane looks like on your specific environment, registry, CI/CD, observability, and governance, in 45 minutes.
Architecture reviews are free. Bring your CTO, your CISO, or your enterprise architect.