In the on-premises deployment scenario, all components required for AI assistant implementation are hosted at the on-premises location.
This deployment option is available with Kubernetes cluster or Docker Compose.
The on-premises deployment option involves the following roles and components:
Script developer: a person who writes scripts that define the dialog and business logic of the conversational experience, manages script deployment, analyzes conversational data and customers’ behavior in interactions with the AI assistant.
Application users: users interacting with the application with the Alan AI SDK embedded. The application users communicate directly with the Action Transformer VM (4) through the client’s DMZ (7).
Alan AI Studio: an interface to the Alan AI Platform, a web-based IDE comprising a script editor, version and deployment control, dialog script testing tools, logs and analytics.
Action Transformer VM: a VM allocated for each AI assistant project. This VM is responsible for dialog management and execution of the business logic defined in the dialog script.
Storage: the Alan AI Studio storage containing dialog scripts with version history, user behavior analytics and statistics.
Conversational services: components responsible for speech recognition and generation.
DMZ: client’s demilitarized zone. The DMZ must have an externally visible IP address with a DNS name through which the Alan AI SDK (2) will connect to the Action Transformer (4) in Docker (8).
Docker: an environment running Alan AI component images on the client’s machine.