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Flexible content moderation system
We tailor the content moderation process according to your business needs.
Moderators have access to a user-friendly interface where they can review all content. They can easily approve appropriate content and block any content that is not suitable.
Integration with external services to simplify moderation tasks
Integration with Google's Cloud Vision API and Yandex Vision
Integration with Toloka and MechanicalTurk for data recognition
Integration with the operator's workspace
Pre-moderation or post-moderation, depending on your tasks
Why is the moderation process hard to implement?
A large volume of content
Moderating a large volume of data is difficult, especially when you do it manually. An efficient interface can speed up the work of the moderator.
Implementation complexity
Automated systems increase the efficiency of a moderator. However, they can take long to develop and implement.
Constant changes
Content can change rapidly. The moderation business process must be flexible to respond quickly to new tasks.
Users create various aliases, use slang, and masking to circumvent moderation systems. It makes difficult to detect unwanted content. For example, you need to create machine learning models recognising such content.
Diversity of content
User content may include text, images, videos, audio, and other formats. Moderating all types requires different approaches, which can complicate business processes.
Aliases and masking
How our solution works
Our system assembles the moderation pipeline from separate entities. Each entity is responsible for a small part of the business process.
We define the necessary pipeline, including integration with existing automated APIs and setting up the moderator's workplace.
Each piece of content goes through the entire algorithm, including automatic and manual filtering, and gets out approved or rejected.
When are standard APIs not enough for automatic moderation?
Sometimes the moderation pipeline is more complex than using only automatic APIs. For instance:
We will set up the entire moderation business process, including access to automatic APIs tailored to your business needs.
When you need to get a response from multiple APIs and react if a contradiction occurs (e.g., send the content for manual moderation.
When you need to detect if the content has changed in order to restart the moderation.
When you need to track at which stage an error occurred.
Contact us to simplify and accelerate content moderation using machine learning. We will answer any questions and develop a solution for your business.