Ship agents your
organization runs on.
A working demo is easy. Production, with simulation, CI/CD, observability, and governance, is where projects stall, and where Lyzr closes the gap.
Framework-agnostic. LangChain, CrewAI, Bedrock, or custom.
50K scenario runs before any agent touches production.
Git-native CI/CD. Versioned, staged, instant rollback.
Every run traced: cost, latency, quality, hallucinations.
RAI policies enforced at inference time, every output.
Improvement Engine loops production back to simulation.
AI and automation teams at these organizations run on Lyzr
What it takes to move an agent
from demo to production estate.
Every AI and automation team knows the moment: the POC looks great, the stakeholders are impressed, and then production reveals the layers nobody planned for. Lyzr is built for that moment. Not the demo, the deployment.
Built on one framework, locked to it
Your team chose LangChain or Bedrock for the POC. Now every new agent inherits that decision, whether or not it fits the use case.
Any framework, one infrastructure layer
LangChain, CrewAI, Bedrock, Autogen, custom SDKs, all connect to Lyzr’s control plane. Your team builds how they build. The infrastructure stays consistent.
Testing is manual and incomplete
A handful of test runs before deployment. Edge cases, adversarial inputs, and domain-specific failures surface in production, in front of users.
50,000 simulations before production
Domain-specific, adversarial, edge-case. Every agent scores Six Sigma reliability before it ships. Failures happen in simulation, not in front of your users.
No visibility once it’s live
You know the agent is running. You do not know what it is costing, whether it is degrading, or where it is failing until someone complains.
Full trace on every run
Latency, token cost, quality, and hallucination score on every execution. You see degradation before a user does, and you know exactly where it happened.
Rollback is a manual fire drill
Something breaks at 2am. Rolling back means hunting for the last stable version, by hand, under pressure, with no audit trail of what changed.
Rollback in one command
Git-native CI/CD means staged deploys and instant, audited rollback. When something breaks, one command restores the last stable version. No fire drill.
The workflows teams are
already automating in production.
These are not prototypes. They are the workflows AI and automation teams have deployed on Lyzr, pulled from real engagement notes across industries.
End-to-End Workflow Automation Agent
Connects systems, routes approvals, handles exceptions, and completes multi-step workflows without human intervention, except where you explicitly require it.
Back-Office Processing Agent
Handles the high-volume, document-heavy, manually-intensive processes that consume your team’s bandwidth: wire processing, document extraction, email triage, reporting reconciliation.
Built to reach production, not just to demo.
Automation that ships.
Infrastructure that holds.
AI and automation teams that deployed Lyzr and moved from POC to production: what they were building, what the infrastructure decision was, and where it landed.
Words from the teams that shipped.
The people who need to
see this alongside you.
The teams that move fastest are the ones that identified the infrastructure gap, built the internal case, and brought the right stakeholders into the conversation at the right time.
The POC is always impressive. The question we have learned to ask early is: who else in your organization needs to see how this gets to production, not just how it works in a sandbox?
CTO / Head of Engineering
They own the infrastructure decisions. The “no rewrite, no migration” story needs to land with them, bring them in early.
EssentialInformation Security / CISO
Data sovereignty, VPC deployment, zero-data-egress, they will ask. Better they hear the answers in an evaluation than find gaps post-deployment.
EssentialHead of AI / Principal Engineer
The technical architecture conversation: simulation engine, CI/CD pipeline, observability layer. It belongs with them, and they validate fastest.
EssentialProduct / Platform Owner
If agents are being embedded into product, the platform owner needs to understand the runtime, the observability surface, and the failure modes.
ImportantWhat to take into
the internal conversation.
The resources AI and automation teams use to evaluate the infrastructure, brief their leadership, and walk into the Lyzr conversation already armed.
Your next agent goes live
in weeks, not quarters.
Bring your current stack and your deployment blockers. We will walk through what the infrastructure layer looks like on your specific environment, simulation, CI/CD, observability, and governance, in 45 minutes.
Architecture reviews are free. Bring whoever makes the technical decision.