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A Robust Labeling Ecosystem
Our efficient processes and our use of powerful tools
ensure the most productive workflow

1. The world's most diverse workforce
We build  the best workforce for you to scale your projects

Over than 1500 women work every day for our client's project and all of them have one goal: to succeed in the projects and to acquire new skills. We find you the right profiles to accelerate your projects.


Our workforce is more than 1,500 women, present in 44 countries, who speak 16 languages and have complementary academic and professional skills

Trained & Coached

We provide complete training to our workforce: generic training on annotation tools and methods + project-specific training, as well as coaching throughout the project

2. Powerful annotation Tools to fit your needs
Yours, ours or partners tools

We have surrounded ourselves with external partners in order to offer complementary tools to our customers and to meet all their needs.

Client's Annotation Tools

We connect our workforce to your tools thanks to our efficient API

Isahit Workforce Management

A complete platform where our workforce annotate your datas

Our Partner's Annotation Tools

We partnered with the most advanced tools in the industry to make your annotation projects a success!

3. Best in class project management team
Scale your annotation project with a dedicated team

A dedicated team to your projects to ensure the best possible results. They monitor your projects from start to finish: recruiting and training the workforce, defining guidelines, monitoring data labeling quality, monitoring compliance with timings, technical support, etc.

Guidelines & instructions tailored for every project
Annotations workflow & feedback loops
Quantified metrics to follow productivity & quality
Internal guaranteed and tests

4. Optimized Processes
Hundreds of projects launched and processes continuously improving

A successful annotation project implies an iteration and a validation phase between the client and our team. At Isahit, we learn how to annotate out of examples and not out of theorical training. A contributor is ready to work on a project once he has been trained on numerous of data and various scenarios.

a. Creation of the pipeline

• Understanding the need
• Definition of the workflow
• Implementation of the project
• APIs configuration

b. Validation phase by iteration

• First test on sample data
• Feedbacks session
• Workflow & instructions adjustment

c. Adjustment phase

• Second Test on a larger volume of data
• Feedbacks session
• Processes & instructions adjustment
• Definition of objectives & quality KPIs

d. Production phase

• Process ramp up
• Continuous training of contributors
• Monitoring of quality & production KPIs