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@@ -12,6 +12,7 @@ partition: build
 | [Bubble](/documentation/platforms/bubble/)              | Development platform for application development with a no-code interface                |
 | [BuildShip](/documentation/platforms/buildship/)        | Low-code visual builder to create APIs, scheduled jobs, and backend workflows.           |
 | [DocsGPT](/documentation/platforms/docsgpt/)            | Tool for ingesting documentation sources and enabling conversations and queries.         |
+| [Keboola](/documentation/platforms/keboola/)            | Data operations platform that unifies data sources, transformations, and ML deployments. |
 | [Kotaemon](/documentation/platforms/kotaemon/)          | Open-source & customizable RAG UI for chatting with your documents.                      |
 | [Make](/documentation/platforms/make/)                  | Cloud platform to build low-code workflows by integrating various software applications. |
 | [Mulesoft Anypoint](/documentation/platforms/mulesoft/) | Integration platform to connect applications, data, and devices across environments.     |
diff --git a/qdrant-landing/content/documentation/platforms/keboola.md b/qdrant-landing/content/documentation/platforms/keboola.md
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@@ -0,0 +1,45 @@
+---
+title: Keboola
+---
+
+# Keboola
+
+[Keboola](https://www.keboola.com/) is a data operations platform that integrates data engineering, analytics, and machine learning tools into a single environment. It helps businesses unify their data sources, transform data, and deploy ML models to production.
+
+## Prerequisites
+
+1. A Qdrant instance to connect to. You can get a free cloud instance at [cloud.qdrant.io](https://cloud.qdrant.io/).
+2. A [Keboola](https://www.keboola.com/) account to develop your data workflows.
+
+## Setting Up
+
+- In your Keboola platform, navigate to the Components section.
+- Find and add the Qdrant component from the component marketplace.
+- Configure the connection to your Qdrant instance using your URL and API key.
+
+## Using Qdrant in Keboola
+
+With Keboola's Qdrant integration, you can:
+
+- **Data Pipeline Integration**: Extract data from any source in Keboola, transform it, and load vector embeddings into Qdrant for semantic search capabilities.
+
+- **Vector Database Management**: Create, manage, and update collections in Qdrant directly from your Keboola workflows.
+
+- **Orchestration**: Schedule and automate your vector database operations as part of your data pipeline.
+
+- **ML Operations**: Combine your machine learning models with vector search capabilities for advanced AI applications.
+
+## Example Use Case
+
+A common use case is to build a RAG (Retrieval Augmented Generation) system where:
+
+1. Data is extracted from multiple sources in Keboola
+2. Text is processed and transformed in Keboola's transformation engine
+3. Embeddings are generated and stored in Qdrant
+4. Applications query the Qdrant vectors for semantic search capabilities
+
+## Further Reading
+
+- [Keboola Documentation](https://help.keboola.com/)
+- [Keboola Academy](https://academy.keboola.com/)
+- [Data Operations with Keboola](https://www.keboola.com/blog/data-operations)