Chat Moderation AI Automation

AIB2BSMBAutomationLLMMLOps
Written By Bruno Carrier

Overview

We delivered a GenAI‑powered moderation assistant that classifies posts as Acceptable, Not Acceptable, or Needs Human Review. The solution reduces manual review volume while sustaining consistent decisions at scale. Through fine‑tuned models and prompt engineering, it provides contextual outcomes aligned with moderation policies. The assistant handles routine cases so moderators focus on nuanced judgments requiring empathy and discretion.

Challenges

Our project addressed two key limitations in language AI. First, ambiguity in natural language (sarcasm, regional expressions, coded language) created interpretation challenges. Second, content guidelines constantly evolve with social context and legal requirements. We implemented a dynamic prompt-based rules engine, allowing our model to adapt to guideline shifts without requiring frequent retraining.

Results and Benefits

Massive reduction in manual moderation volume. Faster review cycles with consistent decisions. Improved policy adherence with an auditable decision trail and configurable rules.

AWS Services

Amazon Bedrock, AWS Lambda, Amazon API Gateway

Customer details

  • Company Name: Care Commons

  • Industry: Healthtech

  • Company Type: Mid-sized Enterprise

  • Location: United States of America

  • Project Timeline: 4 weeks

Bruno Carrier https://benilar.com
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