The enterprise agent platform
you’ve been building toward.
Heads of AI and Chief AI Officers carry a mandate nobody fully prepared them for: build the enterprise agent platform from scratch, make it work across every framework and cloud your organization uses, and have it production-ready before the board loses patience. Lyzr is the platform that gets you there – evaluation to production, with the simulation engine, governance framework, and CI/CD pipeline built in from day one.
Simulation runs – evaluation before any agent reaches your users
LongMemEval benchmark – agent memory and context performance
GPT-4o, Claude, Gemini, Llama – no vendor lock-in, ever
From platform evaluation to first agent in production
Heads of AI and CAIOs at these organizations run Lyzr
Recognized by
Evaluate. Deploy. Improve. At every stage.
The five capabilities Heads of AI need to build and run an enterprise agent platform – not just an experiment environment, but a system that continuously improves and scales. Click through to see what each one looks like in practice.
Platform live. In weeks, not quarters.
The path from platform evaluation to enterprise-wide deployment – with production agents running before the end of the first engagement.
Platform evaluation on your real stack.
Not a generic sandbox. Lyzr evaluates against your specific LLM stack, your cloud environment, your security requirements. NayaOne sandbox or direct VPC access – your choice. Ameriprise ran sandbox evaluation, moved to production in 8 weeks.
Prove the agent before anyone sees it.
50,000 simulation runs on your first agent – domain-specific scenarios, adversarial inputs, policy compliance checks. The evaluation gate doesn’t pass until the agent meets Six Sigma reliability. No shortcuts.
Production. In your environment.
Agent CI/CD pipeline running inside your VPC – Git-native, versioned, staged promotion. Every deployment tracked to the commit. Every rollback one command. Your platform team owns the pipeline from day one.
Platform scales. Agents improve.
Lyzr’s Agent Improvement Engine closes the loop – production traces feed back into simulation, agents improve with every run, and the platform scales horizontally across every team and function that wants to build on it.
Enterprise agent platforms. Already in production.
Heads of AI and CAIOs who built their enterprise agent platform on Lyzr – and the scale they’re running at.
The platform questions that move things forward.
The exact questions Heads of AI and CAIOs asked in the evaluations that became production deployments.
We’re using multiple LLMs – GPT-4o for some agents, Claude for others. Does Lyzr lock us into one model provider?
How does the simulation engine help us evaluate agents before we ship them – and what does “50,000 runs” actually mean in practice?
We have a responsible AI programme in place. How does Lyzr integrate with our existing RAI framework rather than replacing it?
What does the developer experience look like for the engineering teams building agents on our platform?
How does Lyzr handle on-prem and air-gapped requirements for our most sensitive AI workloads?
Take something back to the evaluation.
The technical resources Heads of AI and CAIOs use to evaluate, validate, and build the case for Lyzr as their enterprise agent platform.
Playbook
Template
PlaybookWhat AI leaders say after production.
Your enterprise agent platform. Production-ready in weeks.
Bring your current stack, your evaluation criteria, and your production requirements. We’ll walk through what the platform looks like against your specific environment – simulation, governance, model strategy, and deployment – in 45 minutes.
Platform evaluation calls are free. 45 minutes with Lyzr’s Applied AI team.