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AI for the Enterprise

Generative AI Architecture

Whether you’re building your own models or applying foundation models to your business, data remains the biggest bottleneck to AI.

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Enterprise Generative AI Platform

The only full-stack generative AI platform for your Enterprise, powered by the Scale Data Engine.

Fine-Tuning and RLHF

Adapt best-in-class foundation models to your business and your specific data to build sustainable, successful AI programs and data from your enterprise.

Foundation Models

Scale partners or integrates with all of the leading AI models, from open-source to closed-source, including OpenAI, Anthropic, Google PaLM, Cohere, and more.

Enterprise Data

Scale's Data Engine enables you to integrate your enterprise data into the fold of these models, providing the base for long-term strategic differentiation.

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Scale Data Engine

For AI teams, Scale Data Engine improves your models by improving your data.

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RLHF

Powering the next generation of Generative AI

Scale Generative AI Data Engine powers the most advanced LLMs and generative models in the world through world-class RLHF, data generation, model evaluation, safety, and alignment.

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Data Labeling

The best quality data to fuel the best performing models

Scale has pioneered in the data labeling industry by combining AI-based techniques with human-in-the-loop, delivering labeled data at unprecedented quality, scalability, and efficiency.

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Data Curation

Unearth the most valuable data by intelligently managing your dataset

Scale’s suite of dataset management, testing, model evaluation, and model comparison tools enable you to “label what matters.” Maximize the value of your labeling budget by identifying the highest value data to label, even without ground truth labels.

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Scale Generative AI Platform

The only full-stack platform for powering your Generative AI strategy—including fine-tuning, prompt engineering, security, model safety, model evaluation, and enterprise apps.

Custom LLM

Custom Large Language Models (LLMs)

Fine-tuning, retrieval, and plugins for large language models to improve performance on your most important use cases.

12345678910print"falcon-7b-instruct""I'm opening a pancake restaurant that specializes in unique pancake shapes, colors, and flavors. List 3 quirky names I could name my restaurant."importfrom llmengine Completionresponse = Completion.create( model=, prompt=, max_new_tokens=100, temperature=0.2,)(response.output.text)

spellbook

Large Language Model (LLM) App Platform

Spellbook enables you to build, compare, and ship LLM apps in minutes.

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Parameters
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PromptsI am a very smart computer.
I am able to extract
parameters from inputs
and outputs. Here are some examples of inputs with their correct outputs extracted.		I am a very smart computer.
I am able to, given a
call transcript, predict
whether it contains signs
of insider trading or
not. If there is insider trading, I will output “insider trading”. If there are no signs of insider trading, I will output “not insider trading”. Here are some examples of calls with their correct outputs extracted.
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Case Studies & Resources

We've worked with the world's leading AI teams for years, and delivered more high-quality data than anybody else.

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Customers

We have changed the game of AI data—hear it from our customers.

From RLHF to data labeling to model evaluation to enterprise apps, learn from experts why Scale is key to any AI strategy.

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The U.S. intelligence community has spent an enormous amount of resources on collection but the sheer volume that returns is a huge problem. Scale’s LLMs are the tool that will allow the IC to finally and fully exploit all of that intelligence that has been collected.

Michael Burns

Former Deputy Director of Analysis, Central Intelligence Agency

ChatGPT is a great research capability, but Scale AI’s production-ready LLM not only learned from decades of intelligence collection but also explains how and when it received its mission critical intelligence. That’s an operational imperative to earn commander trust.

Morgan Bishop

Computer Scientist, Air Force Research Laboratory

Scale has a great focus on helping companies improve the quality of their data and the usability of their data. Scale has seen so many different applications of AI across so many different kinds of companies. I think it’s well positioned to help a company assess where it is, what’s the state of its data, what’s the state of its systems, and what kind of capability and preparedness to use sophisticated algorithms.

Jeff Wilke

Retired CEO, Amazon Worldwide Consumer, Amazon Worldwide Consumer

One of the things we love about Scale is the fact that we can fully label the world. We can label 2D bounding boxes, 3D bounding boxes, but also semantic segmentation, including in 3D, to understand as much as possible, including scenarios we don’t foresee today.

Adrien Gaidon

Machine Learning Lead, Toyota Research Institute

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