Guaranteed Task Completion Time
Enterprise-grade SLAs include task completion times and tasks can be rapidly scaled up and down to meet your requirements.
Products
Scale RapidThe fastest way to production-quality labels.
Scale StudioLabeling infrastructure for your workforce.
Scale 3D Sensor FusionAdvanced annotations for LiDAR + RADAR data.
Scale ImageComprehensive annotations for images.
Scale VideoScalable annotations for video data.
Scale TextSophisticated annotations for text-based data.
Scale AudioAudio Annotation and Speech Annotation for NLP.
Scale MappingThe flexible solution to develop your own maps.
Scale Enterprise AIModels to support your business use cases.
Scale NucleusThe mission control for your data
Scale ValidateCompare and understand your models
Scale LaunchShip and track your models in production
Scale Document AITemplate-free ML document processing
Scale Content UnderstandingManage content for better user experiences
Scale SyntheticGenerate synthetic data
Solutions
Resources
Resource Library
Blog
Events
Open Datasets
Interviews
Documentation
Guides
Customers
Pricing
Conference
AI Readiness Report 2022
Company
Text
The sophisticated platform for text annotation.
Use Cases
Natural Language Processing
Information Extraction
Extract structured text information from unstructured or semi-structured content.
• Document Processing
• Topic Modeling
• Product Cataloguing
• Policy Enforcement
Natural Language Generation
Understand text inputs, then generate appropriate responses.
• Search and Ad Relevance
• Question Answering (Virtual Assistants)
• Sentiment & Intent Analysis
• Content Summarization & Moderation
Machine Translation
Automatically translate text inputs into different languages.
• Automated Translation
• Automated Transcription
• Dialogue Generation
• Speech to Text, Text to Speech
How it works
Easy to Start, Optimize and Scale
Named Entity Recognition
Classification
Multi-lingual Transcription
Multi-lingual Data Collection
Please label any people, places, or organizations in the following text.
1client.createNamedentityrecognitionTask({
2 callback_url: 'http://www.example.com/callback',
3 instruction: 'Please label any people, places, or organizations in the following text.',
4 params: {
5 text: "They were delighted by the Hilton's location: surrounded by vibrant nightlife, and in close proximity to major landmarks in Paris. And as luck would have it, Paris Hilton happened to be staying in the room next door!",
6 labels: [
7 {
8 name: 'T_ORG',
9 display_name: 'Organization',
10 },
11 {
12 name: 'T_LOC',
13 display_name: 'Location',
14 },
15 {
16 name: 'T_PERS',
17 display_name: 'Person',
18 },
19 ]
20 },
21}, (err, task) => {
22 // do something with task
23});Run Extraction
Automated Quality Pipeline
Tech-enabled quality assurance systems built into the product to reduce costly human review without sacrificing quality. Customers are also provided transparency in regards to quality with a QA tool and dashboard metrics.
Confidence-Based Consensus
Scale Text combines confidence-based consensus and balanced dataset curation to reduce bias and to surface ambiguities early. For more on how we mitigate bias, take a look at our blog post.
Multi-Lingual Support
A large, globally distributed workforce of highly trained labelers gives Scale Text the flexibility to support multiple languages, regional context and unique expertise.
“OpenAI threw a bunch of tasks at Scale AI with difficult characteristics, including tight latency requirements and significant ambiguity in correct answers. In response, Scale worked closely with us to adjust their QA systems to our needs.”
Geoffrey Irving
Member of Technical Staff, OpenAI
Enterprise Ready
Custom Annual Plans and SLAs
24/7 Development Support
Each enterprise customer is paired with a dedicated engagement manager who will ensure smooth on-boarding and continued data delivery.
Cost Effective
Enterprise engagements provide upfront and volume-based discounts, and is the most cost-effective solution for high-quality labels. Plus with Scale AI, there are no platform fees.
Quality Assurance
Best-In-Class Quality
Super Human Quality
Text tasks submitted to the platform combines confidence-based consensus and balanced dataset curation to reduce bias and surface ambiguities early. All tasks receive additional layers of both ML-based checks and human review based on the quality confidence scores.
The resulting accuracy is consistently higher than what a human or synthetic labeling approach can achieve independently.
