The Lightning Fast API for Custom Content Moderation

There’s a wider variety than ever of content moderation AI services available. Knowing your exact needs will help you find the platform that’s right for your specific business needs.

In this post, we compare the accuracy of various content moderation approaches — blacklists, pre-trained ML models, and custom-trained ML models — on a public Kaggle dataset.

Some examples of how content moderation can benefit your business in unexpected ways.

How do you train, configure, integrate, and monitor an AI-based content moderation system such that it gives your users the best experience while protecting your bottom line?

Online communities need content moderation to thrive, but the diversity of the internet is not fully served by general purpose content moderation APIs. We lay out the need for custom AI-assisted content moderation, look at what such a moderation pipeline would look like, and show how Nyckel makes it significantly easier to build such a pipeline.

A lot of the internet's content is in non-mainstream languages. We look at some things to consider when building content moderation models for multi-lingual content.

Progress through blacklists and pre-trained AI's to full custom-AI content moderation.

Train a text classification model for content moderation using SurgeAI's toxicity dataset.