Run AI on your own hardware, governed by your own policies. Need more capacity? Fall back to a target you choose — your own cloud-hosted LLMs, your external AI providers, or the public PeerLLM network. On your terms, never by default.
Organizations that need modern AI without handing their data — or their bill — to a black box.
Finance, healthcare, legal, and public sector teams that need strict data handling and auditability.
Give every team a governed, single front door to approved models — with access controls and reporting.
Keep sensitive code, datasets, and IP inside your boundary while your teams build with frontier models.
Move from unpredictable per-token bills to dedicated capacity with volume and committed-use pricing.
Everything teams need to run frontier AI with the privacy, governance, and reliability your business demands.
Run on your own hardware — a dedicated pool reserved for your organization and governed by your policies.
Governance and access controls designed to stand up to security reviews.
Deploy PeerLLM entirely inside your own infrastructure — cloud, VPC, or on-premise.
Dedicated people and guaranteed capacity so AI stays fast and available as you grow.
Your hardware handles the load by default. When demand spikes, overflow falls back to a target you choose — so your teams are never blocked, and you stay in control of whether, when, and where it happens.
Every request runs first on your dedicated, private network — your infrastructure, your rules.
A traffic spike, a large batch job, or scheduled maintenance pushes past what your hardware can serve.
Overflow bursts to the target you chose — encrypted, policy-governed, and only when you allow it.
Burst to models you run in your own cloud account — capacity you own, under your controls.
Route overflow to the AI providers you already use and trust, on your existing contracts.
Tap the community-powered network as secure, elastic, on-demand capacity.
PeerLLM for Business runs on your own hardware with the isolation, governance, and support a business needs — with configurable fallback to your own cloud LLMs, external AI providers, or the community-powered public network.
| Community Network | PeerLLM for Business | |
|---|---|---|
| Host pool | Shared, community-powered | Your dedicated hardware |
| Capacity | Elastic shared capacity | Dedicated, with configurable fallback |
| Data path | The secure public network | Stays on your infrastructure |
| Identity & access | Individual accounts | SSO / SAML + role-based access |
| Deployment | Hosted by the network | Your cloud, on-prem, or air-gapped |
| Governance | Built-in | Advanced: audit logs & reporting |
| Support | Community & docs | Dedicated support + uptime SLAs |
| Pricing | Usage-based | Volume & committed-use |
Controls across identity, data, governance, and deployment — the questions your security and procurement teams will ask.
Working toward specific certifications for your industry? Talk to us about your requirements — we'll walk your team through our current posture and roadmap.
Deploy into your own AWS, Azure, or GCP account and VPC.
Run entirely inside your own datacenter and hardware.
Fully offline deployments for the most sensitive environments.
A dedicated private network we host and operate for you.
We stand up a dedicated pool of hosts — in your cloud, your datacenter, or ours — isolated to your organization.
Bring your own models, wire up SSO/SAML, and configure access and audit policies to your standards.
Use the same OpenAI-compatible API your developers already know — backed by dedicated support and SLAs.
By default, your requests run on your own hardware — a dedicated pool within your boundary. If you enable fallback, overflow goes to a target you choose — your own cloud LLMs, an external AI provider, or the public PeerLLM network — encrypted and policy-governed. In self-hosted and on-prem deployments, data never leaves your infrastructure.
Your dedicated hardware handles load by default. When demand exceeds it — a spike, a big batch, or maintenance — you can fall back to a target you choose: your own cloud-hosted LLMs, your external AI providers, or the public PeerLLM network. You control whether fallback is enabled, when it triggers, which target it uses, and which workloads are eligible.
Yes. You can deploy into your own cloud account, your datacenter, or a fully air-gapped environment with no outbound connectivity and no fallback. We'll work with your team on the topology that fits your policies.
You can bring your own models to your private network. We'll help you choose and configure the right models for your workloads during onboarding.
Through the same OpenAI-compatible API used across PeerLLM, so most existing SDKs and tooling work with minimal changes. See the developer guide for details.
We build to compliance-ready foundations — SSO/SAML, audit logging, and network isolation. We do not currently hold formal certifications; for the specific frameworks your industry requires, reach out and we'll walk your team through our current status and roadmap.
PeerLLM for Business moves away from unpredictable per-token billing toward dedicated capacity with volume and committed-use pricing. We'll scope a plan around your expected usage on a call.
Tell us about your use case and we'll walk you through a private deployment, security review, and pricing.
