AI/ML Platform
Streamlining machine learning workflows from experimentation to production
Simplifying AI/ML Development
An end-to-end platform for training, evaluating, and deploying machine learning models
Experiment Tracking
Track and compare model experiments, hyperparameters, and metrics in one place
Model Registry
Version and store trained models with their artifacts and metadata
Automated Training
Schedule and automate model training pipelines with configurable resources
One-Click Deployment
Deploy models to production with automated scaling and monitoring
Technology Stack
Backend
- Python
- FastAPI
- PostgreSQL
- Redis
ML Infrastructure
- PyTorch
- MLflow
- Kubernetes
- Docker
Frontend
- React
- TypeScript
- Tailwind CSS
- Chart.js
System Architecture
Key Components
- Experiment Tracking Service
- Model Registry
- Training Orchestrator
- Deployment Manager
- Monitoring System
Impact & Results
50%
Reduction in model development time
90%
Automated deployment success rate
100+
Models in production