- Primary focus
- Data labeling, RLHF and evaluation infrastructure for AI model builders
- Deployment
- Not specified
- Source model
- Other license
- Pricing model
- contact sales
- API available
- Yes
- Windows desktop
- Not specified
- Mobile app
- Not specified
- Overview
- Scale AI supplies data annotation, human-feedback (RLHF) pipelines, and model evaluation services for training and testing AI models; engagements are sold via direct sales, not self-serve pricing.

| Attribute | ||
|---|---|---|
| Overview | ||
| Primary focus | Data labeling, RLHF and evaluation infrastructure for AI model builders | Managed platform for Ray, scaling AI/ML and Python workloads from a laptop to a cluster. |
| Deployment | Not specified | Self-hosted |
| Source model | Other license | Other license |
| Pricing model | contact sales | paid |
| API available | Yes | Yes |
| Windows desktop | Not specified | Not specified |
| Mobile app | Not specified | Not specified |
| Overview | Scale AI supplies data annotation, human-feedback (RLHF) pipelines, and model evaluation services for training and testing AI models; engagements are sold via direct sales, not self-serve pricing. | Anyscale is the company behind Ray, the open-source distributed computing framework born at UC Berkeley's RISELab. Its managed platform runs training, batch inference, and LLM serving workloads on autoscaling Ray clusters, hosted or in your own cloud (BYOC). |
| Explore further | ||
| Vendor website | Visit vendor ↗ | Visit vendor ↗ |
| ITHub profile | View full profile → | View full profile → |
- Primary focus
- Managed platform for Ray, scaling AI/ML and Python workloads from a laptop to a cluster.
- Deployment
- Self-hosted
- Source model
- Other license
- Pricing model
- paid
- API available
- Yes
- Windows desktop
- Not specified
- Mobile app
- Not specified
- Overview
- Anyscale is the company behind Ray, the open-source distributed computing framework born at UC Berkeley's RISELab. Its managed platform runs training, batch inference, and LLM serving workloads on autoscaling Ray clusters, hosted or in your own cloud (BYOC).
ⓘ Confirm technical details and prices with each vendor before making a decision.