Agent Control Plane · for hyperscalers

One control plane across every hyperscaler

AWS, Google Cloud, and Azure each ship their own agent runtime, and each governs only its own cloud. Lyzr deploys the same agent to AWS Bedrock AgentCore and Google Vertex AI Agent Engine together, with cross-cloud routing, failover, one identity model, and one audit trail. No rebuild. No lock-in.

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AWS ISV AccelerateGoogle Cloud PartnerGartner Cool VendorSOC 2 Type II

One estate, one plane

01Build once

02Ship to AWS or GCP

03Route and fail over

04One audit trail

Enterprises governing their agent estate across clouds on Lyzr

01 / The gap

A control plane per cloud is
not a control plane

Every hyperscaler now ships an agent control plane, and each is strong inside its own boundary. None of them reach across it. The enterprise reality is multi-cloud, so agents end up scattered across AWS, GCP, and Azure, each governed by a different plane, with its own identity model, its own audit trail, and its own deploy path.

AWS Bedrock AgentCore

Excellent inside AWS. It governs agents that run on AWS, and only there.

Governs AWS only

Google Vertex AI Agent Engine

Excellent inside Google Cloud. It governs agents that run on GCP, and only there.

Governs GCP only

Microsoft agent stack

Excellent inside Azure and M365. It governs agents that run there, and only there.

Governs Azure only

Your estate spans all three. One plane is missing.

02 / One plane

Your agents span clouds. Your governance shouldn’t fork.

Lyzr sits above the hyperscalers, not beside them. It deploys natively into each cloud’s agent runtime and unifies all of them under one governed pipeline, one registry, one identity model, and one audit trail.

Deploy targets

Deploys natively into every cloud

AWS Bedrock AgentCore, native runtime
Google Vertex AI Agent Engine, native runtime
Azure Container Apps, supported via containers
Your VPC, on-prem, or air-gapped, full data sovereignty

One control plane

Unified under one governed pipeline

Registry and identity for every agent
Evaluate and simulate before promotion
Govern and audit across every cloud
Route and fail over between clouds

One CI/CD pipeline, any framework in One identity per agent, scoped and revocable One audit trail across AWS and GCP Cross-cloud routing and failover

03 / Capabilities

Built for teams running agents on
more than one cloud

The same agent on AWS and GCP

One artifact, both hyperscalers. Cross-cloud routing sends traffic where it should run, and automatic failover moves it when a region or runtime degrades, all inside a single governed pipeline rather than a bolted-on gateway.

Native hyperscaler runtimes

Deploys natively to AWS Bedrock AgentCore and Google Vertex AI Agent Engine. The pipeline handles the cloud-specific plumbing: VPC, IAM, container registries, and logging. Azure and on-prem run through the same extensible pipeline.

One governed CI/CD pipeline

Security scan, container scan, staged promotion, an evaluation gate, PR-to-prod, one-command rollback, and cloud-aware cleanup on failure. The discipline your engineers already trust for software, applied to every agent on every cloud.

One identity, one audit trail

Every agent gets its own dedicated identity, and the broker is IdP-agnostic across Okta, Entra ID, and ADFS through OIDC and SAML. Every action on every cloud lands in one immutable audit trail.

Runs in your own cloud

The plane deploys inside your AWS VPC, your GCP project, or fully air-gapped, with zero data egress. Sovereignty is architectural from day one, not a setting retrofitted later.

Any framework in

LangGraph, CrewAI, Strands, the Lyzr SDK, or custom code. Point the plane at your repository and it handles the entire path to production, regardless of who built the agent or which cloud it lands on.

04 / The pipeline

Push code. It ships to the
cloud you choose.

Enterprise software has had CI/CD for decades. Agent deployments have not, until now. Every deployment is git-driven, version-tagged, evaluated, and identity-mapped before a single user sees it, on whichever hyperscaler you target.

Agent CI/CD Pipeline · dispute-resolver-v2.4 running

Git push

commit a71a73d

Scan and build

image v2.4.3

Non-prod

AWS or GCP

Eval gate

passed

PR to prod

signed off

Production

deploy live

Route + failover

cross-cloud

RAI scan · policy Hallucination · accuracy Relevance · quality Correctness · validation

Git-driven, no manual handoffs

GitHub and Azure DevOps supported natively
Webhooks trigger the full pipeline on every push
The whole team is always on the latest governed version

Pick a runtime. Deploy.

The same agent ships to AWS or GCP by switching the target
The pipeline adapts VPC, IAM, registries, and logging
On failure, cleanup is cloud-aware, per provider

Nothing ships unevaluated

An automated suite runs against the live non-prod agent
Pass, and a PR opens to prod. Fail, and every resource rolls back
Rollback is a revert to a prior version tag, not a fire drill

05 / The difference

One hyperscaler’s plane,
or all of them unified

The hyperscaler-native control planes are excellent inside their own cloud. The only question that matters is whether your agent estate lives in exactly one. Lyzr deploys into each of them and governs across all of them.

Capability	A single hyperscaler’s plane	Lyzr Control Plane
Cloud coverage	Its own cloud only	AWS and Google Cloud, together
Same agent across clouds	Rebuild and re-govern per cloud	One artifact, deployed to both
Routing and failover	Not across cloud boundaries	Built into the governed pipeline
Framework support	Pulled toward one ecosystem	Any framework, same pipeline
Where it runs	The provider’s managed cloud	Your VPC, on-prem, or air-gapped
Identity model	Native to that ecosystem	IdP-agnostic, one identity per agent
Audit trail	One per cloud	One trail across every cloud
Lock-in	Tied to the hyperscaler	Portable by design

Any framework in, one governed pipeline out

100%

Of deployments versioned and evaluated

Hyperscalers, one artifact, one pipeline

Data leaves your cloud boundary

48h

To the first agent through the full pipeline

06 / In production

Enterprises governing agents
across clouds

Not pilots. Production agent systems, governed from one control plane, inside some of the most demanding enterprise environments in the world.

Corporate venture capital armLive

AgenticOS at scale

An AgenticOS running 200+ agents that automate 15+ VC functions, from deal sourcing and startup evaluation through due diligence and investment memo generation, all in production, every day, across the estate.

200+Agents in production

15+VC functions automated

DailyIn production

OrchestrationAgent StudioControl Plane

Global insurance and advisory leaderLive

Retirement advisory

Customers moved off generic chat tools onto a governed retirement advisor, compliant and running in production for over a year, with hallucination management and a full audit trail at every step.

1 Yr+In production

100%Compliant

BFSIHallucination mgmt

Global industrial groupLive

Marketing at scale

A marketing AgentHub converting knowledge-base uploads into multi-format content, blogs, e-books, and social posts, automatically. Work that used to take weeks now happens in hours.

4×Content output

LiveIn production

Content automationMulti-format

Global payments networkLive

Payments intelligence

Agents automating payments operations, compliance checks, and merchant support workflows, with full traceability, governance, and hallucination management at every step.

FullAudit trail

LiveIn production

PaymentsGovernance

Regulated BPO at scaleLive

Regulated operations

A multi-agent BPO orchestration system handling customer support, compliance monitoring, and back-office processing in a highly regulated environment, with full traceability at every step.

MultiAgent system

LiveRegulated industry

BPO automationCompliance

Bring the one agent that is stuck, and your lowest-scoring control point.

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What leaders say

Words from the people who made the call

“

Every vendor we spoke to had great demos. Lyzr was the only one that could articulate, and then deliver, what happens after the demo. That is a fundamentally different conversation.

VP of TechnologyEnterprise ventures group

“

We needed a governed path from prototype to production that our security and compliance teams would sign off on. Lyzr was the only platform with the architecture to back the promise.

Head of AI InfrastructureGlobal financial services enterprise

“

From zero agents in production to seventeen in six months. The pipeline made it repeatable, the evaluation gate made it trustworthy, and we started having the value conversation instead of the governance one.

Chief Digital OfficerEnterprise technology leader

Security and compliance

Governed in your cloud. On your terms.

The plane runs inside your own cloud, per provider, with zero data egress. Air-gapped and on-premises deployments are supported architecturally from day one, not retrofitted.

SOC 2 Type II GDPR ISO 27001 HIPAA ready VPC-native Zero data egress SSO / SAML Identity per agent Immutable audit logs Air-gap ready

48h

From repository connection to a governed production deployment, for the first agent. Every one after follows the same path, on whichever cloud you target.

Common questions

Questions teams ask before they standardize

Which hyperscaler runtimes are supported natively?

AWS Bedrock AgentCore and Google Vertex AI Agent Engine are native deploy runtimes. The pipeline handles the cloud-specific details for each, including VPC, IAM, container registries, and logging. Azure is supported through Azure Container Apps and a container registry, and the architecture extends to additional runtimes and on-prem.

Can I deploy the same agent to AWS and Google Cloud at once?

Yes. The same agent artifact deploys to both AWS Bedrock AgentCore and Google Vertex AI Agent Engine from one pipeline, with control-plane routing and automatic failover between them. This is uncommon in the market. Most hyperscaler-native planes cannot deploy an agent outside their own cloud.

Do I have to leave the hyperscaler I already use?

No. Lyzr sits above your existing clouds and deploys into them. It runs inside your own AWS VPC or GCP project. You keep your cloud commitments and gain one governed pipeline, one identity model, and one audit trail across all of them.

Does this replace AWS AgentCore or Google Vertex AI Agent Engine?

It complements them. Those runtimes are excellent inside their own cloud. Lyzr deploys onto them and governs across them, so a single agent, or an estate spanning both, moves through one pipeline with a unified registry, evaluation gate, identity, and audit trail. Think of Lyzr as the portability and governance layer above the hyperscalers.

Where does our data go across clouds?

Nowhere it does not already live. The plane deploys inside your own cloud environment, per provider, with zero data egress. Air-gapped and on-premises deployments are supported architecturally from day one, not retrofitted. On failure, cleanup is cloud-aware, so AWS and GCP resources are torn down independently.

Which frameworks can I bring?

Any of them. LangGraph, CrewAI, Strands, the Lyzr SDK, or custom code. Point the Control Plane at your repository and it takes over the path to production, regardless of the framework or the target cloud. All agents appear in the same registry, side by side.

Book a demo

Stop running a control plane per cloud

Bring us the one agent that is stuck and your lowest-scoring control point. We will show you what closing that gap looks like on your stack, across your hyperscalers, in 30 minutes. No slides.