Mystic
Experience High-Performance GPU Inference with AI Power
Lightning AI
Develop, train, and deploy AI models effortlessly with Lightning AI, leveraging PyTorch, modular components, and cloud-based infrastructure
About Lightning AI
A Unified Platform for AI Development
Lightning AI combines all the essential tools for AI product development—from prototyping to deployment—into a single platform. Built for speed and scale, it empowers developers, researchers, and enterprises to bring AI ideas to life faster without managing complex infrastructure.
Trusted by Top Companies and Institutions
Used by organizations like LinkedIn, NVIDIA, Cisco, and Stability AI, Lightning supports large-scale AI model training and deployment across industries. With over 200 million downloads, it’s a proven solution trusted for enterprise-grade performance.
How Lightning AI Works
End-to-End AI Product Lifecycle
From training small language models to deploying full-scale generative AI systems, Lightning AI handles every stage. Users can start from templates, write custom code, or run no-code APIs—instantly—from a web browser.
Seamless Cloud Integration
Lightning AI works on your cloud or theirs. It supports AWS, GCP, and soon Azure, allowing teams to use existing credits while keeping data secure with enterprise compliance protocols like SOC2 and HIPAA.
Core Features of Lightning AI
Lightning Studios for Development
Studios are persistent environments with preinstalled tools and GPU access. Developers can code in a web IDE or connect local editors like VSCode. Studios enable real-time collaboration, large-scale model training, and automated workflows without setup delays.
DevBoxes and GPU Management
DevBoxes act like your personal computer in the cloud. Choose CPUs or GPUs, persist your environments across sessions, and scale up or down without manual configuration. Switching between hardware is seamless, and usage is billed by the second.
AI Training and Deployment Tools
Train Models at Scale
Lightning provides optimized templates and SDKs to run training jobs across multiple GPUs or nodes. Built-in autoscaling ensures resources are only used when needed, significantly cutting cloud costs while speeding up experimentation.
Deploy AI Applications with Ease
Deploying AI models is as simple as launching a template. Developers can host full-code or no-code APIs, run batch jobs, or schedule experiments without needing DevOps support. Real-time cost tracking and monitoring ensure everything stays under budget.
Use Cases and Flexibility
For Startups and Research Labs
Lightning allows startups to iterate faster by removing infrastructure overhead. Academic teams benefit from features like shared Studios, version control, and easy GPU access—making collaboration and publishing results more efficient.
For Enterprises and Scale Operations
Large organizations can deploy Lightning within their VPC, apply RBAC policies, and monitor usage across thousands of projects. Integration with internal tools and automation pipelines helps scale operations while maintaining strict security and governance standards.
Security and Accessibility
Enterprise-Grade Compliance
Lightning AI is SOC2 and HIPAA compliant, ensuring data remains secure at all stages. Teams can bring their own cloud, maintain full control over data, and enable secure SSO with SAML integrations.