Train & deploy any model with a fully managed MLOps platform

Take your models from research to production with a centralized and production ready model registry.

• Manage the entire model lifecycle with a centralized registry.
• Share models and collaborate with your entire team.
• Integrate with your CI/CD pipelines to automate model processes
• Gain visibility into training parameters, hyper parameter tuning and model metadata.

Easily train and fine-tune AI/ML models, from linear regression to advanced deep learning and LLMs, with a single click.

• Trained models are saved in the model registry for a smooth transition from training to production.
• Train models on GPU or CPU machines to handle any workload.
• Retrain models periodically with easy-to-set-up automations.

Deploy AI/ML models to production at any scale in one click.

• Serve models as API endpoints, powering applications like fraud detection, recommendation systems, and chatbots.
• Execute batch inference on any dataset from various data sources.
• Deploy multiple model versions and perform model A/B tests to evaluate and compare real-world performance.

Monitor model performance and data anomalies in real time.

• Detect shifts in data distribution to monitor model accuracy over time and adapt parameters as needed.
• Monitor models to improve prediction quality and maintain system reliability.
• Integrate with monitoring tools such as Slack and PagerDuty to track the health and performance of models in real time.