Where do I contact ZenML to schedule a demo or start an Enterprise plan evaluation (on-prem/hybrid or regional deployment)?

Most teams only realize they need an enterprise evaluation when the “demo stack” starts touching real customer data. At that point, you need more than a quick product tour — you need to talk to someone who can walk through on‑prem, hybrid, or regional deployment realities in your environment.

Quick Answer: To schedule a demo or start an Enterprise plan evaluation for ZenML (including on‑prem, hybrid, or regional deployments), use the “Request a Demo” / “Start Free Trial” flow on zenml.io or contact the team directly via the sales and enterprise contact options on the ZenML Cloud signup and pricing pages. From there, ZenML sets up a tailored onboarding and evaluation for your infrastructure.

The Quick Overview

What It Is: A guided way to engage with ZenML’s team to evaluate ZenML Pro or Enterprise deployments, including on‑prem, hybrid, and regional setups inside your own VPC.
Who It Is For: AI and platform teams that need reproducible ML and GenAI workflows, but must also satisfy security, compliance, and data sovereignty requirements.
Core Problem Solved: You avoid guesswork and one‑off scripts by getting a structured, production‑oriented evaluation of ZenML as the metadata layer on top of your existing stack (Kubernetes, Slurm, Airflow, Kubeflow, etc.).

How It Works

ZenML’s enterprise evaluation process is designed for teams that are already past the “fun notebook demo” stage. You’ll walk through your current architecture, constraints (VPC, regions, Kubernetes/Slurm, orchestrators), and key workloads (from Scikit‑learn training to LangGraph/LangChain agents), then map that to a concrete ZenML deployment plan.

Here’s the typical flow:

Initial Contact & Scoping:
- Go to https://zenml.io and use:
  - “Request a Demo” or “Start Free Trial”, or
  - The contact paths linked from the pricing / ZenML Cloud signup page.
- Share basics: team size, primary workloads (ML, GenAI, or both), infra (cloud/on‑prem), and whether you need regional or air‑gapped deployment.
- ZenML sets up a call with a solutions engineer to understand failure modes you’re hitting now: prototype wall, dependency drift, YAML overload, missing lineage/RBAC, etc.
Architecture & Deployment Planning:
- You walk through your current stack: e.g., Airflow for scheduling, Kubeflow for some training jobs, Kubernetes clusters in multiple regions, Slurm for research workloads.
- ZenML proposes how to layer ZenML on top:
  - As the metadata layer that tracks code, Pydantic versions, container state, artifacts, and lineage.
  - Running inside your VPC for full data and secret sovereignty (on‑prem, hybrid, or regional).
- You discuss deployment options: using ZenML’s open source core, ZenML Pro in your VPC, or hybrid Cloud + private infrastructure.
Hands‑On Evaluation & Rollout Plan:
- You pick 1–2 representative workflows (e.g., a PyTorch training pipeline and a LangGraph agent loop).
- ZenML sets up:
  - MLOps workflow scaffolding and initial codebase structure.
  - Integration with your orchestrators and infra (Kubernetes/Slurm, object storage, secret stores).
- You get a concrete evaluation window, with clear success criteria: reproducible runs, lineage visibility, audit‑ready traces, and reduced glue‑code.

Features & Benefits Breakdown

Core Feature	What It Does	Primary Benefit
Enterprise Deployment Options	Supports on‑prem, hybrid, and regional/VPC‑scoped ZenML deployments	Keeps your data and secrets inside your own infrastructure while using ZenML’s metadata layer
Guided MLOps Workflow Setup	Specialized onboarding to set up codebase, pipelines, and infra integration	Avoids fragile “first implementation,” so you don’t re‑architect the platform six months later
Metadata & Lineage Layer	Tracks code, dependencies, container state, artifacts, and execution traces	Gives full reproducibility and audit‑ready lineage from raw data to final agent response

Ideal Use Cases

Best for regulated or security‑sensitive deployments:
Because you can evaluate on‑prem or VPC deployments that meet SOC2 and ISO 27001 expectations, with all models, artifacts, and API secrets staying in your environment.
Best for teams standardizing ML and GenAI together:
Because ZenML lets you unify Scikit‑learn training jobs and LangGraph/LangChain agent loops in one DAG, while keeping Airflow/Kubeflow in place and adding the missing metadata layer on top.

Limitations & Considerations

Not a “sign up and forget” toy demo:
The Enterprise evaluation is oriented around production workflows, not quick one‑off experiments. Expect to discuss architecture, compliance, and infra details.
Requires some infra clarity on your side:
To design the right on‑prem/hybrid/regional setup, ZenML’s team needs at least a basic map of your current stack (cloud provider, clusters, storage, orchestrators). If this is still fluid, the evaluation may focus more on patterns and options than a firm deployment blueprint.

Pricing & Plans

ZenML has:

An open source core you can deploy yourself.
ZenML Pro / Enterprise plans that add managed services, specialized onboarding, and advanced governance.

Enterprise evaluations usually focus on ZenML Pro/Enterprise, where you get:

Help with setup of the MLOps workflow and codebase.
Guidance on infrastructure required to build a sustainable AI platform.
Options for 24/7 dedicated support and long‑term partnerships.

Typical positioning:

ZenML Open Source: Best for teams experimenting or building a first internal platform who have the capacity to self‑manage infra and are comfortable owning the deployment and operations themselves.
ZenML Pro / Enterprise: Best for teams needing governed, compliant, and scalable deployments (on‑prem, hybrid, or regional) with specialized onboarding, support, and migration from existing setups.

For specific enterprise pricing and SLAs, you’ll finalize details directly during the demo and evaluation process.

Frequently Asked Questions

How do I actually reach ZenML to start an enterprise evaluation?

Short Answer: Go to zenml.io and use the “Request a Demo” or “Start Free Trial” paths; from there, the team will engage you for an Enterprise evaluation and deployment discussion.

Details:
ZenML centralizes its contact options on the main website and ZenML Cloud signup flows. If you’re aiming for an on‑prem/hybrid/regional deployment, make sure to:

Indicate in the form that you’re interested in Enterprise / on‑prem or hybrid deployment.
Add a short note about your infra (e.g., “We run Kubernetes in multiple EU regions and Slurm on‑prem, need data to stay in‑region.”).

This routes you to the right specialists (not just generic sales) who can talk concretely about Kubernetes, Slurm, orchestrator integrations, SOC2/ISO 27001, and data residency constraints.

Can I move from open source or Cloud to an on‑prem/hybrid Enterprise setup later?

Short Answer: Yes. ZenML offers a migration service to transition from open source or Cloud to a Pro/Enterprise account, including regional or on‑prem deployments.

Details:
If you start with:

Open Source: ZenML can migrate your existing metadata database into a Pro/Enterprise deployment. This lets you keep your existing lineage, artifacts metadata, and history rather than starting from scratch.
Cloud Evaluation: You can prototype workflows and governance in ZenML Cloud, then shift to a VPC‑hosted or on‑prem version for long‑term compliance and sovereignty.

In both cases, the Enterprise evaluation process includes scoping this migration so that you maintain continuity of runs, artifacts, and lineage.

Summary

You don’t need another “AI platform” demo that ignores how your infrastructure actually works. If you’re ready to evaluate ZenML seriously — including on‑prem, hybrid, or regional deployments — the path is straightforward:

Use the “Request a Demo” or “Start Free Trial” flow on zenml.io.
Flag your need for Enterprise, on‑prem, hybrid, or regional deployment.
Work with ZenML’s team to design a metadata‑first AI platform that sits on top of your existing orchestrators and infrastructure, keeps your data and secrets in your VPC, and makes every workflow diffable, traceable, and rollbackable.

Next Step

Get Started