> For the complete documentation index, see [llms.txt](https://docs-v3.activeloop.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs-v3.activeloop.ai/v3.8.2/performance-features/deep-memory.md).
# Deep Memory
## How to Use Deep Memory to Improve Retrieval Accuracy in Your LLM Apps
Deep Memory is a suite of tools that enables you to optimize your Vector Store for your use-case and achieve higher accuracy in your LLM apps.
### Embedding Transformation
Deep Memory computes a transformation that converts your embeddings into an embedding space that is tailored for your use case. This increases the accuracy of your Vector Search by up to 22%, which significantly impacts the user experience of your LLM applications.
Furthermore, Deep Memory can also be used to decrease costs by reducing the amount of context `(k)` that must be injected into the LLM prompt to achieve a given accuracy, thereby reducing token usage.
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