About ShaSentra Labs
Building the future of AI infrastructure from the heart of India.
What We Do
ShaSentra Labs provides enterprise-grade AI compute infrastructure that enables developers, researchers, and businesses to build, train, and deploy AI models at scale. Our cloud platform offers GPU/CPU clusters, one-touch deployment, and integrated MLOps tools without the complexity of traditional cloud infrastructure.
Problems We Solve
- • Expensive and complex AI infrastructure setup
- • Limited access to high-performance GPU compute
- • Complicated model deployment and scaling processes
- • Lack of integrated MLOps workflows
- • High cloud costs for AI workloads
Target Audience & Industry Context
AI Startups & Scale-ups
Companies building AI products that need scalable compute without massive upfront infrastructure investments
Enterprise AI Teams
Large organizations implementing AI initiatives across departments requiring reliable, secure infrastructure
Research Institutions
Universities and research labs requiring high-performance computing for AI research and experimentation
Industry Context: The AI infrastructure market is expected to reach $300B by 2030. We compete in the cloud AI platform space alongside AWS SageMaker, Google AI Platform, and Azure ML, but with a focus on simplicity, cost-effectiveness, and developer experience from India.
Meet the Founder
Shathish Warma
Founder & CEO
A visionary technologist and serial entrepreneur with 3+ years in AI/ML infrastructure. Previously led technical teams at enterprise software companies, with expertise in cloud architecture, distributed systems, and AI model deployment. B.Tech in Computer Science. Based in Tiruvannamalai, Tamil Nadu, India.
"AI belongs to everyone, everywhere."
Our Roots in Tiruvannamalai
We draw inspiration from Tiruvannamalai’s heritage to build technology that powers the future.
Global Footprint
Cloud, Edge, and Quantum nodes managed from one unified control plane.
Born in India. Operating globally.
Our Products & Services
Current MVP offerings and development roadmap
✅ Available Now (MVP Stage)
- • GPU/CPU Compute Clusters: NVIDIA H100, A100, RTX series
- • One-Touch Model Deployment: Deploy models with single click
- • Container Orchestration: Docker-based deployments
- • Basic Monitoring & Logging: Real-time resource tracking
- • Web-based Dashboard: Intuitive management interface
- • Pay-per-use Billing: Cost-effective pricing model
- • API Access: Programmatic control of deployments
🚧 Coming Soon (Beta/Development)
- • Advanced MLOps Pipeline: End-to-end model lifecycle
- • Auto-scaling & Load Balancing: Dynamic resource management
- • Model Versioning & Registry: Version control for models
- • Team Collaboration Tools: Multi-user workspace
- • Enterprise SSO Integration: SAML/OAuth support
- • Edge Deployment: Deploy to edge devices
- • Quantum Computing: Hybrid quantum-classical workloads
Development Stage: MVP (Minimum Viable Product)
Our platform is currently in MVP stage with core compute and deployment features operational. We have successfully onboarded early customers and are actively gathering feedback to enhance our offering. Beta features are being tested with select partners before full release. The platform is production-ready for basic AI/ML workloads.
Platform Screenshots
See what users can expect from our platform
Compute Dashboard
Intuitive dashboard for managing GPU/CPU deployments, monitoring resources, and tracking costs.
One-Touch Deployment
Simple deployment wizard that lets you launch AI models with just a few clicks.
Model Studio
Browse and deploy pre-configured AI models from our marketplace.
Resource Monitoring
Real-time monitoring of CPU, GPU, memory usage and performance metrics.
No credit card required • Free tier available • Production ready