Private Cloud AI | Free.ai

Deploy AI models on your own infrastructure. Self-hosted, private, secure.

Specialus GPU diegimas

Įdiegti Free.ai į paskirtus GPU serverius jūsų pageidaujamoje debesijos srityje. Visiška duomenų izoliacija, individualus modelių priegloba ir SLA palaikomas atsiuntimo laikas. Jūsų duomenys niekada neliečia bendros infrastruktūros.

Pradžia

1x NVIDIA A100 (80GB)

  • Įtraukti visi savarankiškai priimti modeliai
  • Iki 50 gretutinių vartotojų
  • 99,5% uptime SLA
  • E. pašto palaikymas
Kontaktų pardavimai

Profesionalus

2x NVIDIA A100 (80GB)

  • Visi modeliai + individualus patikslinimas
  • Iki 200 gretutinių vartotojų
  • 99,9 % atsiuntimo laiko SLA
  • Prioritetinė parama + Palaidų kanalas
  • SSO / SAML integravimas
Kontaktų pardavimai

Įmonė

Pasirinktas GPU klasteris (H100)

  • Neriboti modeliai ir patikslinimas
  • Neribotas gretutinių vartotojų skaičius
  • 99,99% uptime SLA
  • Specializuotos sąskaitos tvarkytojas
  • Galimos pasirinkimo galimybės dėl išankstinių sąlygų
Kontaktų pardavimai

Ką reiškia būti įtrauktam

  • Speciali techninė įranga — No shared GPUs, guaranteed capacity
  • Duomenų izoliacija — Your data never leaves your deployment
  • Regiono pasirinkimas — US, EU, Asia-Pacific, or custom
  • Visi atvirojo kodo modeliai — Pre-loaded and optimized
  • Pasirinkti modeliai — Fine-tune on your data or bring your own
  • Valdomi atnaujinimai — We handle patching and model updates
  • Visas API — Same API as free.ai, on your domain
  • Stebėsena — 24/7 health checks and alerting

DUK

A private cloud deployment gives your organization dedicated GPU servers running Free.ai infrastructure in your preferred cloud region. Your data never touches shared infrastructure, and you get guaranteed compute capacity with an SLA.

Three tiers: Starter (1x A100, up to 50 concurrent users, 99.5% SLA), Professional (2x A100, up to 200 users, 99.9% SLA, SSO, custom fine-tuning), and Enterprise (custom H100 cluster, unlimited users, 99.99% SLA, on-premise option).

We deploy in US, EU, Asia-Pacific, and custom regions based on your compliance requirements. Region selection ensures data residency compliance for regulations like GDPR and HIPAA.

Yes. All self-hosted open-source models are pre-loaded and optimized on your dedicated GPU servers. The Professional and Enterprise tiers also support custom model fine-tuning and bringing your own models.

Your private cloud instance runs on dedicated hardware with no shared resources. Your data never leaves your deployment, is not accessible by other customers, and is not used for training. Full network isolation is included.

Most private cloud deployments go live within 1-2 weeks. Enterprise tier with custom configurations may take longer depending on requirements. Contact sales for a timeline specific to your needs.

Yes, on Professional and Enterprise tiers. You can deploy your own fine-tuned models alongside our standard open-source models. We help with model optimization and deployment configuration.

SSO/SAML integration is included in the Professional and Enterprise tiers. You can connect your identity provider (Okta, Azure AD, Google Workspace) for centralized authentication and access control.

All tiers include 24/7 health checks and alerting. Professional and Enterprise tiers add detailed performance metrics, usage dashboards, and proactive capacity monitoring. We handle all infrastructure maintenance.

Private cloud pricing is based on GPU allocation, region, and SLA level. Contact sales for a custom quote. Pricing is predictable -- fixed monthly cost rather than per-token billing.

Yes. You can upgrade between tiers or add additional GPU capacity as your usage grows. Scaling up is handled by our team with minimal disruption to your service.

Private cloud runs on dedicated hardware in our managed cloud infrastructure. On-premise (Enterprise tier) deploys on your own physical hardware in your own data center. Both offer full data isolation, but on-premise gives you physical control of the servers.

Like this tool? Share it!

Įvertinti šį puslapį