https://peoplefor.ai/

/peoplefor.ai/: People for AI provides expert data labeling services by utilizing skilled labelers and state-of-the-art technology.

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What is https://peoplefor.ai/?

People for AI provides expert data labeling services for training datasets. They employ a team of skilled annotators, utilize advanced labeling tools, and follow a rigorous methodology to guarantee high-quality annotations.

How to use https://peoplefor.ai/?

To access data labeling services from People for AI, reach out to them through their official website or send an email to initiate contact. They will designate a project manager to collaborate with you in understanding your project's specific needs and in establishing a data labeling approach. Upon finalizing the approach, their skilled labelers will begin annotating your dataset utilizing their advanced tools. Throughout the duration of the project, they offer consistent communication and progress reports to guarantee your satisfaction with the outcome.

Features

Specialized data annotators

Use Cases

Microscopy
Self-driving vehicles
Infrastructure
Food and retail

Frequently Asked Questions

People for AI provides expert data labeling services to train datasets. They employ a team of skilled annotators, utilize cutting-edge labeling tools, and follow a rigorous methodology to guarantee top-notch annotations.

To utilize the data labeling services offered by People for AI, reach out to them via their official website or send a direct email. They will designate a project manager to collaborate with you in understanding the specific needs of your project and outlining a suitable data labeling approach. Upon finalizing the approach, their skilled labelers will commence labeling your dataset using advanced, specialized tools. Throughout the duration of the project, they maintain open communication and provide regular progress updates to guarantee your satisfaction with the results.

People for AI provides top-notch data labeling services to multiple sectors with the help of specialized teams, cutting-edge tools, and a well-defined process that guarantees accurate annotations.

Three key factors set People for AI apart from others. They employ skilled labelers on long-term contracts, utilize experienced project managers for handling complex projects, and maintain a robust social responsibility policy.

People for AI can handle labeling for various projects, from very complex ones to the simplest tasks. They employ labelers with diverse skills to match the unique requirements of each project.

Smaller projects need at least 50 to 100 hours for annotation tasks. They can adjust to specific cases based on project details and the volume that needs annotation.

People for AI can meet tight deadlines by expanding the annotation process efficiently while upholding high quality. The exact time will depend on the project requirements, and they can provide a more accurate estimate after evaluating your needs.

The cost of annotation projects differs based on several factors including the level of complexity, the amount of work, the level of expertise needed, and the use of tools for labeling data. On average, the cost is between 5.5€ and 8€ for each hour of annotation.

People for AI is dedicated to upholding mutually agreed quality standards. If the annotation quality is not satisfactory, they provide free re-annotation for up to two rounds.

People for AI is indeed GDPR-compliant. They take client data's privacy and confidentiality very seriously. The company collaborates with major French corporations that handle extremely sensitive missions.

People for AI consists of a team of 6 staff members based in France and 60 staff members based in Madagascar. The team is dedicated to creating a positive social impact and has a robust Corporate Social Responsibility policy in place.

To begin a project with People for AI, reach out to them through their website or send an email to initiate contact. They will then designate a project manager and a specialized annotation team to commence the project, following the definition of the tool and the initial annotation guidelines.

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