> For the complete documentation index, see [llms.txt](https://openledger.gitbook.io/openledger/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://openledger.gitbook.io/openledger/openlora/use-cases.md).

# Use Cases

#### AI Model Deployment at Scale

* Ideal for deploying multiple AI models with minimal resource consumption.
* Enables companies to offer customizable AI assistants with distinct personalities or functions using different LoRA adapters.

#### Cost-Effective AI Serving

* Reduces the need for multiple GPU instances by serving thousands of fine-tuned models on a single GPU.
* Efficient memory utilization minimizes cloud infrastructure costs.

####  Personalization & Fine-Tuning

* Enables personalized AI models where users can fine-tune their own LoRA adapters and deploy them efficiently.
* Supports applications in chatbots, code assistants, and domain-specific NLP solutions.