Programs

OpenVLAN for AI startups

Ship AI products without shipping your infrastructure. Free credits, priority support, and playbooks for securing GPU fleets, agent tooling, and research clusters.

GPUs in three places, one network over all of them

Training rents in the cloud, inference runs in the closet, your laptop is everywhere else. The mesh flattens it: every box dials out, gets a name, and becomes reachable — no VPN appliance between you and the cluster that costs more per hour than your first office.

  • ✓Multi-cloud GPU access without transit-hub spend
  • ✓On-prem training clusters reachable from anywhere
  • ✓Dataset transfers ride the same encrypted mesh
compute — where it lives
train-a100x8cloud · spot fleet21 msDIRECT
infer-l4on-prem · closet rack4 msDIRECT
dev-macbookeverywhere—ON MESH
public ipsexposed ports0NONE

Agents get identities, not the keys to the kingdom

Your agent needs to call three internal tools and one API — so give it exactly that. Every agent runs as its own node with its own scoped policy, and the audit log shows precisely what it touched, when, and on whose behalf.

# agent policy: three tools, nothing else
agent "research-bot" {
  allow: ["vector-db:6333", "doc-index:443"]
  allow: ["api-weather:443"]
  deny: ["tag:prod"] # default anyway
}

What's included

Everything a seed-to-Series-B AI team needs to run a serious tailnet from day one.

$1,000 in credits

One year of Premium features — SSO, ACLs, session recording — at no cost while you're in the program.

Priority support

Direct channel to the engineers who build the product, with startup-friendly response times.

GPU & cluster playbooks

Reference architectures for multi-cloud GPU access, on-prem training clusters, and inference fleets.

Agent & MCP guidance

Patterns for letting AI agents reach internal tools safely — scoped identities, per-agent ACLs, audit trails.

Co-marketing

Joint case study, logo placement, and introductions to our cloud and investor ecosystem.

Community access

Private channel with other AI builders in the program, plus early access to new features.

Why AI teams pick OpenVLAN

Reach GPUs anywhere

Training in the cloud, inference on-prem, laptops everywhere — one flat, encrypted network over all of it.

No inbound holes

Nothing to attack: nodes dial out, no public IPs, no bastion sprawl, no port scanning surface.

Identity for agents

Give every agent its own device identity and policy, with a full audit log of what it touched.

Eligibility

Requirements

  • Building an AI-native product or model
  • Under 50 employees, under $10M raised
  • Less than 3 years old
  • Not already on an enterprise plan

Apply

Tell us what you're building and your infrastructure stack. We review weekly and reply within five business days.

AI program FAQs

What counts as "AI-native"?
You're building a model, an agent product, or AI-first tooling. Using a chatbot for support doesn't qualify; shipping inference as part of your product does. When in doubt, apply and describe what you're building.
Can the credits cover GPU costs?
The credits apply to OpenVLAN plans and features, not cloud compute — but the GPU playbooks show you how to reach rented or owned GPUs privately, which often saves more than the compute itself.
Do you help with agent security reviews?
Yes — program members get the agent & MCP guidance plus office hours where we review scoped-identity setups with your engineers. Enterprise customers pay for this; program startups get it included.
Is there a catch on the credits?
One year of Premium, then standard pricing with startup discounts if you qualify for the general program. We'd rather you build something great on the mesh than audit our fine print.
Our whole team is remote across four time zones — problem?
That's the point. The mesh doesn't care where anyone sits; your SSO handles who's in, and the audit log handles what they did.