Accelerate ML model development, at scale
The potential of machine learning technologies is creating a cross-industry race to develop and deploy quickly. Give your team the best tools to experiment and deliver better performing models faster to fuel business growth.
Trusted by 30,000+ ML practitioners and teams
Let your team focus on the science
Enable them to manage ML projects the right way
Best practices for ML efficiency
- Git like workflow for the whole project
- All ML life cycle components (data, code, experiments, annotations) in one place
- Easy Collaboration
- Increase ML teams flexibility by reducing their reliance on DevOps
Explainability & Reproducibility of production models
- Data & model lineage
- Automated data, code and model versioning to guarantee accurate reproducibility
- Data visibility for explainability, debugging and ethical AI
Accelerate experimentation cycles
- Active learning pipelines out of the box
- Query & filter inference data to generate training-ready datasets
- Data management for fine-tuning of generative AI models
- Auto labeling
Seamless ML Stack integration
- Connect to any cloud provider storage
- Integrate with orchestration, monitoring and compute tools & resources that you already use
- Two way sync with your existing code repositories
Governance & security
- On prem/VPC installations
- User access controls
- Separated project instances