MLnative

Features

• Fractional GPU Autoscaling: Adjust memory and scaling for each model to meet demand, optimizing GPU resource allocation.
  
• Priority-based Rate Limiting: Ensure service quality with configurable request quotas and priority settings for enterprise clients.
  
• Easy, Automatable Deployments: Containerize and publish ML models swiftly with REST API or web UI, simplifying the deployment process.
  
• Seamless Integration: Deploy any major ML framework models without code alterations, ensuring smooth integration.
  
• Cloud Agnostic Solution: Install MLnative across major cloud services or on-premise while maintaining complete control over your data.
  
• Comprehensive Security: Secure your data with built-in scanning, audit logs, and SSO within your controlled environment.
  

Use Cases:

• Real-time Inferences: Deploy machine learning models that require immediate results, with minimal latency even during peak times.
  
• Multiple Model Management: Handle a variety of models in production simultaneously with ease, thanks to flexible configuration options.
  
• Generative AI Applications: Utilize MLnative for cutting-edge generative AI tasks, including LLM, Text to Speech, and Computer Vision.
  
• Data Security Compliance: Ensure data remains within company networks, offering an ideal solution for sensitive data management.
  

MLnative stands out as a robust, adaptable, and secure platform for managing complex machine learning tasks in production with confidence. Its user-centric design caters to high-performance demands with ease.