Stream’s AI Moderation helps apps and platforms detect, classify, and manage harmful user-generated content at scale. It acts as a real-time assistant for moderators and admins scanning messages, applying rules, and surfacing risks before they escalate into bigger issues.
Why Use AI for Moderation?
The core idea is simple: instead of relying entirely on humans to spot hate speech, grooming attempts, spam, or graphic content, Stream’s AI automatically reviews each message and flags anything that violates your community standards.
This significantly reduces manual moderation workloads. Rather than scanning through thousands of messages, AI will immediately act against clear harms, while your human moderators can focus on edge cases and high-risk scenarios.
Shifting to AI improves response time and lowers operational costs. AI moderation is faster and more scalable than human-only review, especially for high-volume platforms or apps with 24/7 activity.
Beyond speed and cost, AI improves coverage. It can spot issues that involve nuance, sarcasm, coded language, and more, making it a powerful tool for identifying emerging risks and enforcing evolving community standards with greater consistency.
How AI Moderation Works
Stream AI Moderation works by processing each message through a large language model (LLM) that’s been fine-tuned for trust and safety use cases. Unlike basic keyword filtering systems, this model analyzes the full context of each message, including tone, intent, and the past 10 messages sent to determine whether the content is harmful.
For example, it can tell the difference between a playful joke and a targeted insult. This contextual awareness helps reduce false positives and build trust in automated moderation decisions.
Here’s how it works in real-time:
As soon as a message is sent, it’s instantly passed through the AI engine. In a matter of milliseconds, the model evaluates the message and assigns a label (sexual harassment, threat, etc.) that reflects why the AI detected this message as harmful.
Based on your configuration, the system then applies an action.
- If the content is safe, it’s posted to the channel immediately.
- If risky, the content will be flagged, blocked, shadowbanned, or otherwise based on your configuration and sent to the moderation queue.
This real-time decision flow enables platforms to take immediate action when needed. By combining speed, precision, and flexibility, Stream gives you a scalable system that adapts to your needs without compromising safety or user experience.
What You’ll See in the Dashboard
All AI decisions, whether flagged, blocked, or approved, flow into the Stream Dashboard for review. Each message is tagged with key attributes such as:
- A harm label (e.g., harassment, threat, self-harm)
- An action already taken (e.g., flag, block, shadowban)
- A severity level that reflects the potential risk (low, medium, high, critical)
These signals give your team a quick way to prioritize what matters most and avoid wasting time on benign content.
When moderators click into a flagged message, they can see the full conversation thread, user metadata, and account history. This context helps them decide whether to approve the content, escalate, or take stronger action like banning a user.
In later modules, we’ll walk through the dashboard in detail and show you how Admins and Moderators use these tools day to day.
Designed for Global Communities
AI Moderation is built to support global and multilingual communities. It detects policy violations across multiple languages and identifies evolving threats like slang or obfuscation.
What’s Next
In upcoming lessons, you’ll see how all of this fits together, starting with how to assign roles and navigate the dashboard and progressing to policies, workflows, and reporting.