Introduction
At People for AI, we do more than just provide data annotation; we build expert teams dedicated to the success of your artificial intelligence projects. But how do we do it? Contrary to common belief, our process is much more than a simple matchmaking service. It is a complex alchemy of expertise, commitment, and collaboration.
In this article, we’ll give you a look inside our process to explain how we guarantee the quality and accuracy of your data.
1. Long-Term Commitment: The Core of Our Model
One of the cornerstones of our approach is our relationship with our annotators. We prioritize individuals who are committed for the long term. Why? Because data annotation, especially for complex projects, isn’t a one-time job. It requires a deep understanding of the instructions, progressive skill development, and consistent rigor.
Working with annotators over the long term allows us to build valuable project knowledge and expertise, ensuring both unrivaled consistency and quality. Furthermore, it provides our recruits with stable employment and a healthy, respectful work environment.
2. Tailored Selection: The Ideal Annotator for Each Project
Every AI project is unique, as are the skills required to annotate it. That’s why we don’t select our annotators at random.
Our matching process is precise and rigorous, taking into account several key criteria:
- Data Type: Is the data videos, images, or text? We identify annotators with specific experience in those formats.
- Task Type: Semantic segmentation, object detection, or transcription all require different skills. We match the annotator to the task that best fits their abilities.
- Sector-Specific Experience: For projects in niche fields (automotive, 3D, sports, healthcare, etc.), we prioritize annotators who already have knowledge of the sector, which makes it easier to understand the data and what’s at stake.
- Personal Aptitudes: We carefully evaluate qualities like rigor, attention to detail, and curiosity.
3. Seamless collaboration: the connection between annotators and production project managers
Once the annotation team is in place, the magic happens through close collaboration with our production project managers. They are not just simple coordinators; they are the guarantors of quality.
Their role is to:
- Manage projects: They ensure that deadlines and the quality of deliverables are met.
- Answer questions: They are the direct point of contact for annotators if there are any doubts about instructions.
- Provide feedback: They regularly analyze the quality of the annotation and provide constructive feedback to improve team performance.
- Facilitate communication: They create a continuous link between the annotators and the France team, ensuring that the client’s expectations are perfectly understood and applied in the field.
4. The Strategic Link with the France Team: Where Expertise Meets Execution
Our project managers, based in France, are the core of our operations. They define strategies, translate complex client needs into clear instructions for annotators, and validate the final data quality.
The constant dialogue between the production project managers on the ground and the experts in France ensures a continuous feedback loop, enabling real-time adjustments and optimal quality, from project conception to final delivery.
Conclusion
At People for AI, our model is based on a strong belief: the quality of annotated data is directly proportional to the commitment and expertise of the people who process it. By investing in long-term relationships with our annotators, conducting a rigorous selection process, and creating seamless collaboration among all stakeholders, we don’t just provide annotation.
We deliver confidence. And it’s this confidence that makes all the difference for the success of your AI projects.
