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+---
+stage: none
+group: unassigned
+info: To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/product/ux/technical-writing/#assignments
+---
+
+# AI Architecture (Experiment)
+
+GitLab has created a common set of tools to support our product groups and their utilization of AI. Our goals with this common architecture are:
+
+1. Increase the velocity of feature teams by providing a set of high quality, ready to use tools
+1. Ability to switch underlying technologies quickly and easily
+
+AI is moving very quickly, and we need to be able to keep pace with changes in the area. We have built an [abstraction layer](../../ee/development/ai_features.md) to do this, allowing us to take a more "pluggable" approach to the underlying models, data stores, and other technologies.
+
+The following diagram shows a simplified view of how the different components in GitLab interact. The abstraction layer helps avoid code duplication within the REST APIs within the `AI API` block.
+
+```plantuml
+@startuml
+skin rose
+
+package "Code Suggestions" {
+  node "Model Gateway"
+  node "Triton Inference Server" as Triton
+}
+
+package "Code Suggestions Models"  as CSM {
+  node "codegen"
+  node "PaLM"
+}
+
+package "Suggested Reviewers" {
+  node "Model Gateway (SR)"
+  node "Extractor"
+  node "Serving Model"
+}
+
+package "AI API" as AIF {
+  node "OpenAI"
+  node "Vertex AI"
+}
+
+package GitLab { 
+  node "Web IDE"
+
+  package "Web" {
+    node "REST API"
+    node "GraphQL"
+  }
+
+  package "Jobs" {
+    node "Sidekiq"
+  }
+}
+
+package Databases {
+  node "Vector Database"
+  node "PostgreSQL"
+}
+
+node "VSCode"
+
+"Model Gateway" --> Triton
+Triton --> CSM
+GitLab --> Databases
+VSCode --> "Model Gateway"
+"Web IDE" --> "Model Gateway"
+"Web IDE" --> "GraphQL"
+"Web IDE" --> "REST API"
+"Model Gateway" -[#blue]--> "REST API": user authorized?
+
+"Sidekiq" --> AIF
+Web --> AIF
+
+"Model Gateway (SR)" --> "REST API"
+"Model Gateway (SR)" --> "Serving Model"
+"Extractor" --> "GraphQL"
+"Sidekiq" --> "Model Gateway (SR)"
+
+@enduml
+```
+
+## SaaS-based AI abstraction layer
+
+GitLab currently operates a cloud-hosted AI architecture. We are exploring how self-managed instances integrate with it.
+
+There are two primary reasons for this: the best AI models are cloud-based as they often depend on specialized hardware designed for this purpose, and operating self-managed infrastructure capable of AI at-scale and with appropriate performance is a significant undertaking. We are actively [tracking self-managed customers interested in AI](https://gitlab.com/gitlab-org/gitlab/-/issues/409183). 
+
+## Supported technologies
+
+As part of the AI working group, we have been investigating various technologies and vetting them. Below is a list of the tools which have been reviewed and already approved for use within the GitLab application.
+
+It is possible to utilize other models or technologies, however they will need to go through a review process prior to use. Use the [AI Project Proposal template](https://gitlab.com/gitlab-org/gitlab/-/issues/new?issuable_template=AI%20Project%20Proposal) as part of your idea and include the new tools required to support it.
+
+### Models
+
+The following models have been approved for use:
+
+- [OpenAI models](https://platform.openai.com/docs/models)
+- Google's [Vertex AI](https://cloud.google.com/vertex-ai) and [model garden](https://cloud.google.com/model-garden)
+- [AI Code Suggestions](https://gitlab.com/gitlab-org/modelops/applied-ml/code-suggestions/ai-assist/-/tree/main)
+- [Suggested reviewer](https://gitlab.com/gitlab-org/modelops/applied-ml/applied-ml-updates/-/issues/10)
+
+### Vector stores
+
+The following vector stores have been approved for use:
+
+- [`pgvector`](https://github.com/pgvector/pgvector) is a Postgres extension adding support for storing vector embeddings and calculating ANN (approximate nearest neighbor).