Overview

Hello! Welcome to Scale AI documentation.

We are excited to work with you to accelerate the development of AI. Explore our documentation to quickly deliver value from your AI investments with high quality data.

Scale Pro

Scale Pro is the high-leverage data platform for AI-enabled businesses. We provide best-in-class customer experience through labeling products and concepts that come from the future, clean powerful interfaces, flexible tools and platforms to enable fast iteration, and the highest model improvement/$ ratio in the industry.

✅ Seamlessly initiate labeling with our API
✅ Work with dedicated Engagement Managers who will help you set up labeling projects fully customized for your use case
✅ Scalably label production volumes of data, including complex 3D and Sensor Fusion data formats
✅ Receive the highest quality labeled data, guaranteed (via SLAs)

Nucleus

Nucleus is the ultimate dataset management tool for machine learning teams looking to go beyond surface-level model evaluations. Nucleus helps you dig deeper into your data, correct failure points, and improve overall model accuracy. With Nucleus you can:

✅ Visualize and analyze data at scale
✅ Curate and focus on the most important dataset segments
✅ Review and refine annotations
✅ Measure and enhance model performance

Nucleus brings your data and predictions together, empowering you to solve data quality issues, fix failure modes, and create better models faster.

Gen AI Platform

The Scale GenAI Platform enables enterprises to quickly develop, test, and deploy Generative AI applications tailored to custom use cases using proprietary data. With tools for connecting data, fine-tuning models, and secure deployment, it provides a flexible and scalable solution for enterprise needs, allowing you to:

✅ Implement optimized RAG pipelines and fine-tuned models with the Scale Data Engine.
✅ Deploy open and closed-source models, including OpenAI, Cohere, and Meta.
✅ Securely launch AI applications in your VPC with support for AWS and Azure.
✅ Fine-tune models to enhance performance, reduce latency, and optimize token usage.
✅ Test, evaluate, and monitor AI systems with advanced metrics and tools to ensure quality and reliability.