Shakti Studio is an MLOps platform for deploying, serving, and optimizing AI models with superior performance, scalability, and cost-efficiency. Our custom inference engine intelligently adapts to your specific requirements, whether you need lower latency, higher throughput, or cost savings; allowing you to focus on building exceptional AI product experiences without the burden of managing complex infrastructure.Documentation Index
Fetch the complete documentation index at: https://docs.shaktistudio.ai/llms.txt
Use this file to discover all available pages before exploring further.
How Shakti Studio Works
Shakti Studio provides an end-to-end solution for AI model deployment and optimization through a comprehensive suite of services:Deploy Models Your Way
Serverless Endpoint
Get started immediately with multiple pre-deployed models in our marketplace. Access popular open-source models like Llama, Mistral, and more with simple pay-as-you-go pricing.
Dedicated Endpoint
Deploy custom models (open-source or proprietary) on your private cloud or Shakti Studio infrastructure with full control over resources, scaling, and configuration.
Customize
Fine-Tuning
Train models on your data with blazing-fast speed. Deploy fine-tuned models immediately for inference with the similar performance as base models.
Quick Start Guides
Choose from these common workflows to get started with Shakti Studio quickly:Inference
Call deployed models via API for real-time predictions
Deployment
Deploy and scale your own models on dedicated infrastructure
What You Can Build
Real-time AI Applications
Power chatbots, assistants, and interactive experiences with sub-500ms latency
Custom AI Solutions
Fine-tune models on your domain-specific data for significantly improved accuracy
Enterprise GenAI
Scale large language models securely on your infrastructure or ours
Production ML Systems
Deploy and monitor models with built-in observability and autoscaling
Next Steps
Sign Up
Create an account and get your API key to start building
Explore APIs
Review our API Reference for detailed integration guides
Fine-Tune Models
Follow the Fine-Tuning guide to customize models for your use case