How do I sign up for VESSL AI and create an org for team billing?

Most teams hit the same wall: you finally find GPUs you can afford, then get blocked by sign-up friction, unclear org settings, or messy personal vs. team billing. VESSL AI is built to remove that overhead so you can get from “no account” to “team-ready org with shared billing” in minutes.

This guide walks through, step by step, how to:

Sign up for VESSL AI
Create an organization for your team
Configure team billing so GPU spend is centralized and controlled

Throughout, assume you’re trying to stand up a sane, auditable setup for LLM post-training, Physical AI, or AI-for-Science workloads without turning into a full-time “job wrangler.”

Why use an org for team billing?

You can kick the tires on VESSL AI as an individual, but the moment more than one person is running jobs, you want an org:

Centralized billing: All GPU usage (Spot, On-Demand, Reserved) rolls up to one invoice instead of scattered personal cards.
Shared resources: Shared storage, projects, and configurations instead of everyone rebuilding environments.
Access control: Clean separation between personal experiments and company workloads.
Procurement-ready: Easier to plug into corporate finance processes, SLAs, and compliance reviews.

Think of your org as the control plane for your team’s GPUs—one place to manage users, workloads, and spend across providers and regions.

Step 1 – Create your VESSL AI account

You have two main paths: sign up via the Web Console or start from the CLI and link your account.

Option A: Sign up via Web Console

Go to the VESSL AI website
- Visit https://vessl.ai and open the Web Console / Get Started entry point.
Choose your sign-up method
- Use your work email (recommended for team billing) or a supported SSO option if available for your company.
Verify your email
- Check your inbox for a verification email. Click the link to activate your account.
Complete basic profile info
- Add your name and (ideally) your company name and role.
- This helps align you with the correct org later, especially if multiple teams from your company use VESSL AI.

Option B: Start from CLI and link later

If you prefer to live in a terminal:

Install the CLI
- Follow instructions from the VESSL AI docs to install the vessl CLI on your machine.
Run an auth command
- Use something like:
```
vessl auth login
```
- This will open a browser window or prompt you to log in / create an account.
Finish sign-up in the browser
- The flow is essentially the same as the Web Console: verify email, complete profile, and then you’re ready to create or join an org.

At this point, you have a personal account, but not yet a shared org with team billing.

Step 2 – Decide: create a new org or join an existing one

Before you create anything, confirm if your company already has an org:

If your team already uses VESSL AI:
Ask an existing admin to invite you to the org. You’ll inherit the team’s billing and permissions.
If you’re the first person from your company:
You’ll create a fresh org and act as the initial org owner/admin.

Using your work email domain helps VESSL AI associate you with the right organization and can make admin approval smoother.

Step 3 – Create an org for your team

Once you’re logged into the Web Console:

Open the org / workspace menu
- Look for your current context (often your personal space) in the top navigation or sidebar.
- Click it to open the organization selector.
Select “Create New Organization”
- Choose the option to create a new org or workspace for your team/company.
Name your org clearly
Use a name your teammates will instantly recognize:
- Acme AI
- Hyundai – Autonomous Driving
- Berkeley AI Lab
Set the primary region or default settings (if prompted)
- You can still access multiple providers/regions, but choosing a default helps keep early jobs consistent.

When creation completes, you’re now operating inside the org context—not just your personal account.

Step 4 – Configure team billing for the org

Now you need to attach billing so your org can actually consume multi-cloud GPUs through VESSL AI.

4.1 Open billing settings

In the Web Console, ensure you’re in the correct org (not your personal account).
Navigate to Settings → Billing or similar (exact label may vary slightly depending on UI updates).

4.2 Add a payment method

You’ll typically see options like:

Credit or debit card: Fastest way to get started; ideal for early-stage teams and labs.
Invoicing / PO-based billing: For enterprises and government or large academic programs (usually requires talking to sales / support).
Reserved capacity agreement: For guaranteed access and discounts up to ~40% with commitment.

To get going immediately:

Add a corporate card
- Enter card details and billing address aligned with your company.
Set currency and billing preferences
- Choose the right currency if available.
- Confirm contact emails for invoices and billing notifications (e.g., finops@company.com, ap@company.com).

4.3 Align billing with GPU usage patterns

VESSL AI packages GPU capacity into three operational modes. When you set up billing, plan how your team will use each:

Spot:
- Best for: large experiments, hyperparameter sweeps, non-critical training.
- Tradeoff: can be preempted; you save money but risk interruptions.
On-Demand:
- Best for: production services and long-running jobs where reliability matters.
- Benefit: automatic failover across providers/regions for high availability.
Reserved:
- Best for: mission-critical workloads and predictable, heavy usage.
- Benefit: guaranteed high-end GPU capacity (A100/H100/H200/B200/GB200/B300) with discounted rates and dedicated support.

Design your billing expectations around these tiers, so there are no surprises when you scale from 1 to 100 GPUs.

Step 5 – Invite your team into the org

With billing in place, you want everyone running workloads under the same org, not their personal accounts.

5.1 Add members

Go to Org Settings → Members / Team.
Click Invite members.
Enter work emails for:
- ML engineers
- Researchers
- Infra/SRE
- Finance/FinOps (view-only, if supported)
Assign roles (examples, depending on the product’s role model):
- Org Admin: manages billing, org settings, and user roles.
- Project Owner / Maintainer: can create projects, manage workloads, and configure resources.
- Member / User: can run jobs but doesn’t touch billing.
- Read-only / Billing viewer: can monitor usage and invoices, but not execute workloads.

5.2 Encourage CLI and Web Console usage

Tell your team:

Web Console: for creating clusters, viewing jobs, monitoring runs, and checking billing/usage at a glance.
CLI (vessl run): for native workflows, automation, and CI/CD pipelines.

Everything should be tied back to the same org, so GPU usage and storage are tracked centrally.

Step 6 – Keep billing clean: projects, tags, and monitoring

Once multiple teams are running jobs, you’ll want enough structure to understand who used what and why.

6.1 Use projects per team or workload

Inside your org, create projects such as:

llm-post-training
physical-ai-robotics
ai-for-science-simulations
demo-env / sandboxes

This helps you:

Separate experimental workloads from production.
Pivot cost by team, product area, or research track.

6.2 Use labels/tags for cost attribution

When launching jobs (via Web Console or CLI), apply labels/tags like:

team=nlp
env=prod / env=research
project=autonomous-driving

Finance and infra teams can then filter usage reports by tag to answer “who burned 40 H100-hours last night?” in seconds.

6.3 Monitor usage and spend

In Billing / Usage views, you should be able to:

See hourly or daily GPU consumption by SKU (A100 vs. H100 vs. H200, etc.).
Break down usage by Spot / On-Demand / Reserved.
Export data or connect with your reporting system.

When in doubt, aim to structure data so FinOps doesn’t need to ping you for screenshots.

Step 7 – Connect with sales for Reserved capacity and SLAs

If you’re moving beyond “initial tests” into “this model is production-critical,” it’s time to tighten guarantees.

Consider talking to VESSL AI sales if you need:

Reserved GPU capacity for A100/H100/H200/B200/GB200/B300 at specific scales and regions.
SLAs and custom terms suitable for enterprise or government procurement.
Onboarding & custom integrations with your existing infra or security stack.
Academic programs for university labs and research groups.

This typically builds on top of your existing org and billing setup, not a separate account.

Common questions about sign-up and org billing

Can I start personally and later move to an org?

Yes. You can:

Start with a personal account to explore the Web Console and CLI.
Later create an org, set up billing, and move active work into projects under the org.
Ask VESSL AI support to help migrate or consolidate resources if needed.

Can I belong to multiple orgs?

Typically yes, especially if you:

Work on a company project and a university lab project.
Provide consulting across multiple clients.

Always double-check that you’re in the correct org context before launching high-cost jobs.

Who should own billing?

In most teams:

An Org Admin from infra, DevOps, or FinOps owns billing settings.
Engineers and researchers run jobs within projects but don’t manage payment methods.
Finance gets read-only access to view invoices and usage.

This separation keeps governance clean while letting engineers move fast.

Final checkpoint: what “done” looks like

You’ve successfully signed up for VESSL AI and created an org for team billing when:

You can log in and see your org name in the top context.
The org has a valid payment method and billing contacts set.
Your teammates are invited, assigned roles, and can run jobs.
Jobs launched via Web Console or vessl run show up under the org, not just your personal space.
You can open Billing / Usage and clearly see GPU consumption and spend trends.

From here, the goal is simple: spend less time on “job wrangling” and more time on experiment design, analysis, and shipping real AI systems.

Next Step

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