
iMerit - Alternatives & Competitors
Multimodal AI Data Solutions
iMerit offers software-delivered services combining automation, human expertise, and analytics for AI data annotation and model fine-tuning across various industries.
Ranked by Relevance
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1
SuperAnnotate The AI data platform that simplifies and accelerates model-building
SuperAnnotate is an enterprise-grade platform for AI data annotation, model fine-tuning, and dataset management that enables organizations to build, evaluate, and deploy AI models faster and more efficiently.
- Freemium
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2
DataVLab AI-Powered Data Labeling & Image Annotation
DataVLab offers scalable and ethical data labeling services, including image, video, and 3D annotation, to enhance AI and machine learning models. Their AI-assisted process ensures high-quality, efficient results across various industries.
- Contact for Pricing
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3
Keylabs State-of-the-art data annotation platform for machine learning
Keylabs is a comprehensive data annotation platform that combines AI-assisted tools for image and video labeling with advanced management capabilities. The platform offers high-precision annotation services across multiple industries with up to 99.9% accuracy.
- Free Trial
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4
Sigma AI High-Quality Data Annotation for Generative AI and LLMs
Sigma AI provides high-quality data annotation services for training Generative AI and Large Language Models (LLMs). They offer data labelling, strategy, collection, and human-in-the-loop processes.
- Contact for Pricing
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5
Toloka AI Empower AI Development and LLM Fine-Tuning
Toloka AI provides expert data for SFT and RLHF, offering access to skilled experts in over 20 domains and 40 languages to elevate your machine learning models.
- Contact for Pricing
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Kili Technology Build Better Data, Now.
Kili Technology is a data-centric AI platform providing tools and services for creating high-quality training datasets and evaluating LLMs. It streamlines the data labeling process and offers expert-led project management for machine learning projects.
- Freemium
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