Locally hosted and controlled
Run Seed AI on a GPU-enabled Windows Server managed by your organization and located inside your own environment.
Self-hosted AI platform for business
Private AI. Your network. Your control.
Give your team a company-approved AI workspace powered by locally hosted models without sending every prompt, document, and conversation to an outside provider.
Local GPU inference
Administrator-controlled connections
Built for business teams
Explore Seed AI
Learn about the platform.
Choose where to start.
Explore the Seed AI private AI platform based on what you need to know next. Review the features, understand private AI, plan your infrastructure, or see pricing and deployment.
AI
01
Platform Features
Explore Seed AI Features
See the private AI workspace, locally hosted models, knowledge bases, AI agents, tools, integrations, user management, and administrative controls.
View Features
PRIV
02
Private AI Explained
What Is Private AI?
Learn how private AI gives businesses more control over where models run, where company information lives, who can access it, and what outside services may connect.
Learn About Private AI
GPU
03
Infrastructure
Review System Requirements
Review GPU, VRAM, system memory, storage, Windows Server, model size, concurrency, and other infrastructure considerations for running Seed AI.
View Requirements
GET
04
Pricing & Deployment
Get Seed AI
Review implementation pricing, annual platform licensing, additional user capacity, deployment services, and the process for bringing Seed AI into your organization.
Pricing & Get Seed AI
Why Seed AI?
Local AI at the core.
Control where it connects.
Run your own LLMs
Upload supported GGUF models and run inference locally on your own GPU hardware.
Built for business teams
Manage users, roles, and permissions so each person has access to the right models, agents, and information.
Private knowledge bases
Upload internal documents and let your team query approved company knowledge in plain language.
Custom agents and tools
Build agents for specific teams and workflows. Add local capabilities or approved API tools as needed.
Predictable annual licensing
Run Seed AI on infrastructure you control with predictable annual platform licensing and no per-prompt or per-message fees from Seed AI.
Deployment Process
How Seed AI works.
From server planning to launch, Seed AI can be deployed in five clear steps.
Plan your GPU server
Tell us which models you want to run. We can provide the appropriate server, GPU, memory, and storage specifications.
Install Seed AI
Install Seed AI on your Windows Server with assistance for IIS, GPU drivers, application setup, and testing.
Upload GGUF models
Add supported GGUF files through the model manager and configure how each model uses your GPU resources.
Configure users and tools
Set up permissions, agents, prompt templates, knowledge bases, and approved API connections.
Train your team and launch
Train your staff, establish company AI policies, and begin using Seed AI throughout your organization.
Controlled Connectivity
Keep local work local. Approve outside connections when needed.
Seed AI gives your staff a company-approved AI workspace powered by locally hosted models. When an agent needs an external service, optional API tools can be configured and controlled by your administrators.
Local GPU inference
Locally stored GGUF models
Private document storage
Internal chat history
Administrator-controlled API tools
Role-based access
Explore Private AI
Bring AI In-House
Local AI. Controlled connections.
Give your team practical AI tools while keeping your models, documents, knowledge bases, users, and core AI workspace on infrastructure your company controls.