# Planning a private enterprise AI deployment

Source page: https://www.finogeeks.com/en/knowledge/private-ai-deployment
Language: en

Prepare a deployment checklist covering models, execution environments, identity, system interfaces, data flows and operational ownership.

## Map runtime locations and data flows

Identify where clients, server-side agents, knowledge and business systems run. Establish which information enters model requests and which results are written back. Use this map to plan networking, storage and access policies.

## Prepare the integration checklist

Combine FinAIOS products around the project requirements. Assign configuration and maintenance responsibilities separately for hosting, clients, skills, knowledge and security.

- Models: identify self-hosted or available services and data handling requirements.

- Identity: map organizations, users, tenants and service accounts.

- Systems: prepare API or MCP interfaces, permissions and test environments.

- Security: define file and network boundaries, credentials, approvals and records.

- Operations: assign deployment, monitoring, backup, update and incident ownership.

## Validate in the actual environment

Check operating systems, CPU architectures, databases and network requirements against the current product version and adaptation documentation. Validate model calls, retrieval, tool execution, approvals and result queries with real tasks rather than installation alone.

## Related products and solutions

Explore the product mechanisms and application details behind this guide.

- Domestic IT and private deployment

- FinHub

- FinDesk

- FinGuard

## Related resources

- [View all guides](https://www.finogeeks.com/en/knowledge)