One governance layer.
Every agent you own.

Your organization has agents running across clouds, teams, and frameworks. Lyzr gives CIOs a single governance layer over all of them – registry, observability, responsible AI guardrails, and a full audit trail. Without rebuilding a single agent.

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85%

Agent projects reaching production under Lyzr governance

1,000+

Enterprise agents under active governance right now

48h

To deploy the governance layer across your existing agent estate

Zero

Data egress from your cloud boundary. Runs entirely inside your VPC.

CIOs at these organizations have deployed Lyzr

Recognized by

Gartner Cool Vendor 2024
G2 Leader – AI Agents
AWS ISV Accelerate
IDC Innovator
SOC 2 Type II
HIPAA Ready
GDPR Compliant
What strong AI governance looks like

Secure. Responsible. Completely yours.

CIOs who govern their AI estate well have five things in place. Click through to see what each one means in practice – and what it looks like when Lyzr is running it.

How CIOs deploy Lyzr

From your current estate to governed, in weeks.

Lyzr sits above what you already have. No agent rebuilds. No cloud migrations. The governance layer comes to your environment – not the other way around.

01Connect

Your estate connects. Nothing moves.

AWS Bedrock, Azure AI Foundry, GCP Vertex, LangChain, CrewAI, custom builds –
all connect to the control plane. Your agents stay exactly where they run today.

48 hours
02Register

The first full picture of your agent fleet.

Every agent gets a registry entry: named owner, version, access scope,
framework, and cloud. Most CIOs see their complete AI estate for the first time.

Week 1
03Govern

Responsible AI policies applied across all agents.

RBAC, hallucination guards, PII masking, approval workflows – enforced across every
agent in your estate regardless of who built it or which framework it runs on.

Week 2-4
04Defend

Every decision on record. Permanently.

Full trace on every agent run. Any decision reconstructable step-by-step. Compliance
exports in one click. Your board, your auditors, your regulators – answered.

Ongoing
CIOs who made the call

Governed in production. At enterprise scale.

Not evaluations. Not proofs of concept. CIOs who deployed Lyzr’s governance layer across their AI estate – and the outcomes that followed.

Ameriprise Financial
Wealth Management · Regulated
Control PlaneMulti-modelMulti-cloud
“Enterprise AI agent orchestration and central governance. Values faster AI dev cycles, guardrails, simulation, and monitoring.” – Ameriprise evaluation notes
Live
In production
Full
Audit trail
Wells Fargo
Financial Services · Enterprise
Governance layerGuardrailsMulti-framework
“Lyzr as enterprise agent infrastructure – governance, guardrails, simulation, auditability, and multi-model support alongside their internal AI gateway.”
$250K
Engagement
CIO-led
Evaluation
WTW
Insurance · Benefits · BFSI
Governed pipelineCompliant1yr+ live
“Our agent has been live for over a year without a compliance incident. Lyzr is the governance layer that makes regulated AI possible.”
1yr+
In production
Zero
Incidents
Itaú Unibanco
Banking · Global · Multi-runtime
Multi-runtimePolicy enforcement
“Centralized policy enforcement, agent runtime governance, multichannel orchestration – across multiple runtimes and internal platform efforts.”
Global
Deployment
Multi
Runtime
Live Nation
Entertainment · Heterogeneous AI
OpenAIAnthropicDatabricks Genie
“Unified observability, monitoring, token quotas, and governance across a heterogeneous AI environment.” One control plane. Three vendors.
3
Vendors, 1 plane
Live
In production
Firstsource (GRC)
BPO · ANZ · Compliance
GRC automationCompliance monitoring
“Regulatory compliance monitoring and mitigation” – governance-first deployment inside one of the most compliance-intensive BPO environments in ANZ.
$360K
Engagement
Live
In production
Questions leaders ask before they say yes

The questions that move the decision forward.

These are the exact questions CIOs asked in the evaluations that became production deployments.

We have agents on Bedrock and Azure AI Foundry. Does deploying Lyzr require migrating or rebuilding anything?
Nothing rebuilds. Nothing migrates. Lyzr’s control plane connects to your existing agent infrastructure – Bedrock, Foundry, LangChain, CrewAI, custom runtimes – and adds the governance layer above it. Your agents stay on the infrastructure you chose. Ameriprise ran a sandbox evaluation and moved to production governance in under eight weeks. Their agents never moved.
Our data cannot leave our cloud boundary under any circumstances. How does Lyzr’s architecture handle that?
Lyzr deploys inside your VPC. The control plane runs in your cloud. Zero data leaves your boundary. Agent traces, decisions, outputs, and logs stay inside your environment. For the highest-security requirements – air-gapped, zero external connectivity – Lyzr Optimus is physical on-prem hardware. Accenture Federal Services and government agencies run this configuration.
When the board or a regulator asks what our AI did and why – what does that audit actually look like?
Every agent run is logged with a full trace: which agent, which version, what inputs, what tools it called, what output it produced, which responsible AI policies it passed. Any decision reconstructable in minutes. Compliance exports are one click, formatted for regulatory review. WTW has been running fully audited for over a year with zero compliance incidents.
We have OpenAI, Anthropic, and Azure running in different parts of the organization. Can one governance layer actually cover all of it?
Yes – and this is exactly why CIOs with heterogeneous environments choose Lyzr. One registry. One policy engine. Every agent. Live Nation governs agents built on OpenAI, Anthropic, and Databricks Genie from a single Lyzr control plane. The framework doesn’t matter. The cloud doesn’t matter. The governance layer is consistent across all of it.
What does responsible AI actually mean in practice – not the policy, the actual enforcement?
Responsible AI in Lyzr means enforcement, not documentation. Every agent output passes a RAI check before it reaches a user: hallucination scoring against your ground truth, PII detection and automatic masking, policy compliance checking, and configurable block/flag/reroute rules. The policy you write is the policy that runs – on every output, every time.
For CIOs

Take something back to the table.

The materials CIOs use to build the case – for their security teams, their boards, and their procurement reviews.

How to Build Your Agentic AI Roadmap in 2026Playbook
Playbook
How to Build Your Agentic AI Roadmap in 2026
How to Build Your Agentic AI Roadmap in 2026 | Architect by Lyzr
Explore Playbook
101 Enterprise AI Use Cases You Can Deploy TodayTemplate
Template
101 Enterprise AI Use Cases You Can Deploy Today
Inside: 100+ production-ready AI agent use cases across Marketing, Sales, HR, Banking, Insurance.
Explore Template
How to take agents to productionPlaybook
Playbook
How to take agents to production
A practical guide to turn AI prototypes into reliable, production-ready agents
Explore Playbook
Words from the people who made the call

What CIOs say after production.

“Lyzr didn’t just give us a platform – they gave us a team that understood what production-grade AI actually means in a regulated environment. Our agent has been live for over a year without a compliance incident.”

Head of Digital
WTW – Willis Towers Watson

“Every AI vendor we spoke to had great demos. Lyzr was the only one that could articulate – and then deliver – what happens after the demo. That’s a fundamentally different conversation.”

VP of Technology
Accenture Ventures

Your environment. Governed from day one.

Bring your current architecture. We’ll show you what the governance layer looks like on your specific estate – no generic demo, no hypothetical stack.

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Architecture reviews are free. 45 minutes with Lyzr’s Applied AI team.