# How Data Extends AI (/docs/data/how-data-complements-ai)



Data does not replace AI. It complements it by adding the data movement, analytical storage, streaming, and BI services that some AI solutions need around the AI layer.

## Core Relationship [#core-relationship]

| Layer      | Main role                                   |
| ---------- | ------------------------------------------- |
| Foundation | Runs and secures the platform               |
| AI         | Serves and manages GenAI capabilities       |
| Data       | Adds enterprise data and analytics services |

## Practical Extension Points [#practical-extension-points]

* `Airbyte` helps bring data into the wider platform from external systems
* `Kafka` supports event-driven data movement and streaming use cases
* `Kubeflow` provides ML pipeline orchestration and notebook-based development
* `Lakekeeper` and `Spark Operator` provide catalog-backed Iceberg processing
* `Tuples` applies tenant data configuration and optional audit publication
* `Superset` exposes business-facing dashboards and BI views over analytical data

## What This Enables [#what-this-enables]

* AI systems that depend on synchronized enterprise data
* Analytics and reporting experiences around platform data
* Event-driven architectures that connect AI and data services
* A cleaner separation between AI application logic and enterprise data operations