Enter RYAX Serverless GPUs
When demand on GPU utilization increases with the advent of LLMs Large Language Models and the democratization of AI in general, and face to rigid pricing policies of traditional Cloud providers for the usage of GPUs,
Ryax enables you to build AI applications on serverless GPU, design data workflows and APIs, without managing infrastructure nor code deployment
RYAX Serverless GPUs feature enables faster AI-based, Cloud application deployment enhanced with usage of custom open-source AI models inference and fine-tuning.
Leverage GPUs in a serverless way meaning that users will not have to worry neither about the infrastructure provisioning nor about the environment preparation for executions on GPUs; They just bring their code and the rest is handled by Ryax.
Take advantage of automated, simplified usage of GPUs resources for AI executions leveraging on a pay-per-second usage.
Build inference or fine-tuning workflows for the usage of Large Language Models (LLM) / Foundation Models (FM) based on pre-configured environments for AI executions on GPUs ready to be adapted to your particular code and requirements.
Enable the custom creation of APIs for different tasks related to AI models operations such as inference, training and fine-tuning
Develop, deploy and monitor complete Cloud-native applications using finely-integrated AI models (inference, training, fine-tuning) through the low-code functionalities of Ryax platform.
Time to market: Serverless services such Lambda, Cloud functions, Fargate accelerate the Cloud application creation since they enable usage of the infrastructure with no related operations to be handled by the user. Ryax Serverless GPUs feature enables faster AI-based, Cloud application deployment enhanced with usage of custom open-source AI models inference and fine-tuning.
Usage simplification: Usage of GPUs for AI models inference and fine-tuning needs a specialized software stack environment preparation (CUDA, Pytorch, Tensorflow, etc) which is complex for non-experts. Ryax Serverless GPUs feature abstracts the complexity of preparing the software stack on the GPUs through pre-configured environments, for open-source AI models inference and fine-tuning; while allowing the simplified creation of APIs and fine-integration in the context of Cloud applications through the powerful low-code features of Ryax.
Cost to market: The per-minute payment of most known Cloud providers' GPUs usage services along with complexity of using them (data engineering expertise) keeps the cost of using GPUs for inference and fine-tuning on known Cloud providers' quite high. Ryax Serverless GPUs feature enable a per-second payment for GPUs which through the automated software stack environment preparation, the adapted autoscaling capabilities and the fine-integration in Cloud applications and APIs creation enable low-cost usage of custom AI services.