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isahit

Isahit provides an ethical data labeling platform that utilizes a human-in-the-loop approach to ensure high-quality, bias-free annotations for AI training across various datasets, including computer vision and natural language processing. The platform addresses the need for accurate data labeling while creating meaningful job opportunities in developing countries, thereby promoting social impact.

Paris, FranceFounded 2016
Updated 4 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Many AI and machine learning projects require large volumes of accurately labeled data, but obtaining this data can be expensive, time-consuming, and prone to biases if not handled carefully. Traditional data labeling processes often lack transparency and may not adequately address ethical concerns related to worker compensation and data privacy.

Solution

Isahit provides a data labeling platform that combines human-in-the-loop expertise with AI-assisted tools to deliver high-quality, bias-free training data for machine learning models. The platform offers a managed workforce of trained labelers, primarily women in developing countries, who are fairly compensated for their work. Isahit supports a wide range of data types, including images, videos, text, and audio, and offers tailored workflows for various AI applications, including computer vision, natural language processing, and generative AI. By integrating ethical outsourcing practices with an agile technology platform, Isahit enables organizations to scale their AI initiatives responsibly while ensuring data accuracy and model fairness.

Target Audience

Isahit primarily serves data science teams and innovation directors in industries such as automotive, healthcare, retail, and finance who require high-quality, ethically sourced data for their AI and machine learning projects.

Features

  • Human-in-the-loop data labeling services for computer vision, NLP, and audio data
  • Managed workforce of trained labelers with a focus on ethical compensation and social impact
  • AI-assisted labeling tools to improve efficiency and accuracy
  • Support for various annotation methods, including image annotation, video annotation, and text annotation
  • Tailored workflows for specific AI applications, such as LLM fine-tuning and RAG optimization
  • Active learning workflows for smart data labeling
  • Workforce management platform for RLHF (Reinforcement Learning from Human Feedback)
  • Secure API for integration with existing systems
This profile is AI-generated and may contain inaccuracies.