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A Deep Dive into Filtering & Moderation Layer Guardrails

Workshop
Are your filtering and moderation layers precise enough to stop harmful content without blocking legitimate use cases?

Moderation guardrails often fail not because filters are missing, but because policies, configurations, and escalation paths are underspecified or poorly monitored. This workshop examines how moderation layers actually behave under real-world ambiguity and scale. 

To win, your GenAI systems must apply clear moderation policies through well-tuned filters, escalation paths, and continuous monitoring. 

The Challenge

When filtering and moderation layers are weak or inconsistently designed, teams struggle to maintain safety and reliability. 
• Policy drift: Moderation policies are vague or inconsistently applied across filters and services. 
• Ambiguity handling: Gray-area content triggers unreliable decisions, leading to over-blocking or unsafe passes. 
• Blind spots: Teams lack visibility into false positives, appeals, and long-term effectiveness of moderation controls. 
These failures increase user frustration, safety risk, and operational burden as systems scale. 

Our Solution

In this hands-on workshop, your team designs and evaluates robust filtering and moderation guardrails through applied exercises and real-world scenarios. 
• Establish clear moderation layer policies aligned to intended use and risk tolerance. 
• Configure filters to detect and block harmful content across common categories. 
• Analyze and handle gray-area and ambiguous cases using structured decision patterns. 
• Design appeals and escalation paths for contested moderation outcomes. 
• Monitor moderation effectiveness and false positives using practical metrics and review loops. 

Area of Focus
  • Establishing Moderation Layer Policies 
  • Configuring Filters for Harmful Content 
  • Handling Gray Area and Ambiguous Cases 
  • Managing Appeals and Escalation Paths 
  • Monitoring Effectiveness and False Positives 
Participants Will

• Define actionable moderation policies that translate cleanly into technical controls. 
• Configure and tune filters to balance safety coverage with usability. 
• Apply consistent approaches to ambiguous and borderline content cases. 
• Design escalation and appeal flows that reduce operational friction. 
• Evaluate moderation performance using effectiveness and false-positive signals. 

Who Should Attend:

AI EngineerTechnical Product ManagersML EngineersPlatform EngineersEngineering Managers

Solution Essentials

Format

Virtual or in-person

Duration

4 hours 

Skill Level

Intermediate 

Tools

Moderation policy frameworks, filtering configurations, and analysis exercises 

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