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AZURE X AI

Add AI Content Moderation with Azure & Gemini

Build the same real-time content filter used by Twitch, Discord, and Match Group

Start Building
Add AI Content Moderation with Azure & Gemini project preview
Gemini API
Azure Functions

Difficulty

Mildly spicy

Time to complete

60 minutes

Availability

Free

BUILD

What you'll build

Create a production-grade content moderation API that classifies toxic messages in milliseconds. Learn how platforms processing millions of messages daily filter harmful content with AI.

1. Connect Your App to Gemini AI

Get a Gemini API key from Google AI Studio and add it to your Azure Function App settings for secure access.

2. Add AI Moderation to Your API

Create a moderation module that sends messages to Gemini for real-time classification and integrate it with your POST endpoint.

3. Watch Your AI Block Toxic Messages

Deploy your updated function, test with toxic and clean messages, and review violations in Cosmos DB Data Explorer.

4. Build a Moderator Dashboard API

Create endpoints for human moderators to review flagged content, overturn false positives, and track AI decisions.

Your portfolio builds as you work.

Every project documents itself as you go. Finish the work, and your proof is ready to share.

PROJECT

Real world application

Skills you'll learn

  • AI Classification

    Design prompts that make AI reliably categorize content

  • Content Moderation

    Filter toxic, spam, and harassment in real-time

  • Violations Tracking

    Store flagged messages for moderator review

  • API Integration

    Connect serverless functions to external AI services

  • Fail-Open Patterns

    Build resilient systems that degrade gracefully

  • Human-in-the-Loop

    Design review workflows for AI-assisted decisions

Tech stack

  • Gemini API logo

    Gemini API

    Google AI that powers multimodal understanding and content classification at scale.

  • Azure Functions logo

    Azure Functions

    Serverless compute platform that runs code on-demand without managing infrastructure.

I finally understand how platforms like Discord moderate millions of messages. Building the AI classification prompts myself made everything click.

Marcus Chen

Platform Engineer

OUTCOME

Where this leads.

Relevant Jobs

Roles where these skills matter:

  • AI/ML Engineer
  • Trust & Safety Engineer
  • Platform Engineer
  • Cloud Developer

Azure x AI

Add AI moderation to any chat system you build. Protect online communities with the same real-time content filtering used by Twitch and Discord at scale.

Azure x AI

Continue the Journey

FAQs

Everything you need to know

This is Part 2 of the 4-part Azure x AI Series. Start with Part 1: Build a Streaming Backend on Azure to set up your Function App and Cosmos DB. After this project, continue with Part 3: Handle Streaming Events at Scale and Part 4: Deploy with Azure DevOps.

Yes, this project builds on Part 1: Build a Streaming Backend on Azure. You need an existing Azure Function App with a POST /message endpoint and Cosmos DB connection. The tutorial includes a catch-up section if you need to set up these prerequisites, but completing Part 1 first provides the best learning experience.

Google AI Studio offers a free tier with 1,500 requests per day - plenty for building and testing your moderation system. This entire NextWork project uses zero-cost tiers for both Gemini API and Azure Functions. You can complete the project without a credit card or cloud spending.

The fail-open pattern means that if AI moderation fails (API down, parsing error, etc.), messages are allowed through rather than blocked. This prevents a Gemini outage from breaking your entire chat system. Production platforms use this approach because blocking all messages during an AI failure is worse than temporarily allowing unmoderated content. The tutorial teaches you how to implement this resilient pattern.

AI moderation using Gemini significantly outperforms traditional keyword filters. Gemini understands context - it can detect sarcasm, hate speech disguised as humor, and harmful stereotypes that simple filters miss. Platforms like Stream (used by Match Group and Midjourney) report 90% less circumvention and 80% fewer fraudulent messages with AI moderation. This project teaches you how to design prompts that maximize classification accuracy.

No AI is perfect - sometimes it blocks legitimate messages (false positives) or misses subtle harassment. The Secret Mission teaches you to build a moderator dashboard API where humans can review flagged content, overturn AI decisions, and track what's being caught. This is the same pattern used by Twitch's AutoMod, Discord's moderation bots, and YouTube's content filters.

Yes, this project builds a production-ready moderation system. The Gemini integration, violations tracking, and moderator review API are the same patterns used by platforms handling millions of messages daily. For production use, you would add rate limiting, adjust the classification prompt for your specific community guidelines, and potentially add escalation workflows for edge cases.

One Project. Real Skills.

60 minutes from now, you'll have completed Add AI Content Moderation with Azure & Gemini. No prior experience needed. Just step-by-step guidance and a real project for your portfolio.

Let's Build This

Mildly spicy level