SOLUTIONS
Scalable Labeling for Machine Learning and Business Processes
Crowd.It revolutionizes data labeling by leveraging gamified crowdsourcing and a global network of multilingual talent to deliver high-quality, scalable annotation solutions. Through anonymized snippets and consensus-driven models, Sophia ensures exceptional accuracy across diverse datasets while keeping costs at a minimum.
HUMAN CAPITAL
Sophia Crowd is a versatile, AI-driven platform for accurate and efficient labelling across a wide range of use cases. From building high-quality machine-learning datasets to streamlining back-office services, Sophia enables organizations to handle complex labelling tasks at scale.
Key Challenges in Data Annotation:
High Costs: Traditional labeling methods often come with significant expenses, particularly for multilingual datasets or large-scale tasks.
Speed and Scale: Rapidly processing data across global markets while maintaining accuracy can be a logistical challenge.
Quality Assurance: Ensuring consistency and precision without costly rework is critical for operational success.
Whether for building machine-learning datasets, back-office processes, or any labeling task, Crowd.It provides an innovative approach to scale operations while maintaining the highest quality standards.
Gamified Crowdsourcing for Scale
Consensus-Driven Accuracy
Multilingual Capability
Fast Turnaround with Quality Control
Scale from Labelling to Knowledge Work
50-100M
8 yrs
30%
99.5%
Data Annotation with Better Quality, and Better Service
Here's what sets Sophia label apart
Gamified Efficiency
Engaging and intuitive interfaces keep contributors motivated, ensuring fast turnaround times without compromising quality.
Lowest Cost Per Task
By tapping into distributed talent and optimizing workflows, Sophia reduces costs significantly compared to traditional labeling methods.
Nearly a Decade of Experience
With years of experience in data annotation and automation, Sophia has been delivering high-quality, scalable solutions since 2017.
Consensus-Validated Accuracy
Proprietary consensus models deliver unmatched precision, eliminating errors and ensuring data integrity.
Flexible Use Cases
Supports tasks ranging from machine learning dataset creation to back-office operations and customer service categorization.
Scalable and Secure
Processes millions of annotations seamlessly while safeguarding data privacy with ISO 27001 compliance and global standards adherence.
Business Lead, Major Global Back Office Service Provider
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