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SEAL Leaderboards
✓ verifiedFree
Scale AI provides training data and evaluation platforms; major AI company.
👁 625K/mo♥ 3.0K
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GitFluence
Free
Pricing
No public pricing
No public pricing
No public pricing
DEVELOPER: FREE
STARTER: $119 / month
GROWTH: $599 / month
ENTERPRISE: Starting at $1,800 / month
No public pricing
Core features
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦High-quality training data for AI models
- ✦Scale Data Engine for data management and labeling
- ✦Scale GenAI Platform for full-stack Generative AI
- ✦Scale Donovan for AI-powered decision-making
- ✦AI model evaluation and red teaming
- ✦RLHF (Reinforcement Learning from Human Feedback)
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- ✦Developer-first platform for AI-powered integrations
- ✦Secure, isolated sandboxes for running JavaScript/Python code
- ✦Automatic management of npm/PyPI dependencies
- ✦Built-in platform plumbing: secrets, webhooks, scheduling, logs, and audit
- ✦Yep Agent (prompt → runnable processes)
- ✦MCP Server/Tools (convert code into AI agent tools)
- ✦Serverless runtime (YepCode Run) and SDK access
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Use cases
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Developing self-driving car AI with high-quality training data.
- →Building Generative AI applications using the Scale GenAI Platform.
- →Improving AI model performance through supervised fine-tuning and RLHF.
- →Evaluating the safety and robustness of AI models using SEAL Leaderboards.
- →Integrating enterprise data into foundation models for strategic differentiation.
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- →Building complex API integrations that require custom code and logic beyond what no-code tools offer.
- →Safely running AI-generated scripts in isolated environments with secrets management.
- →Automating workflows that require large datasets, loops, branching, or custom dependencies.
- →Connecting AI agents to external databases, APIs, and services using MCP tools.
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