> For the complete documentation index, see [llms.txt](https://docs.impossiblecloud.com/impossible-cloud-help/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.impossiblecloud.com/impossible-cloud-help/integrations-with-other-applications/ai-and-machine-learning-integrations-guide.md).
# AI & Machine Learning Integrations Guides
Impossible Cloud Storage integrates seamlessly with leading AI and machine learning frameworks and tools. Since Impossible Cloud is S3-compatible, these tools can use it as a backend for vector databases, experiment tracking, and dataset storage without any additional configuration changes. The following overview lists integrations that have been verified by Impossible Cloud.
| Application | Status | Type | Certification | Guide | Video |
|---|
| LanceDB | 🟢 | S3-compatible | Tested by IC | Link | / |
| Milvus | 🟢 | S3-compatible | Tested by IC | Link | / |
| MLflow | 🟢 | S3-compatible | Tested by IC | Link | / |
| Hugging Face Datasets | 🟢 | S3-compatible | Tested by IC | Link | / |
Since Impossible Cloud is S3-compatible, many other AI and machine learning tools that are not on this list work seamlessly as well. If you are interested in using such a solution, simply fill in [this form](https://share-eu1.hsforms.com/2fuVtex8tSdWrg2Gg6VLijQfbd8d) and we will provide you with compatibility advice for any available solution on the market.
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