{
  "id": 2559888,
  "title": "Presentation: SafeChat: Building AI-Powered Safety Systems at Scale in a Real-Time Marketplace",
  "url": "https://urgent.news/2026/08/22/presentation-safechat-building-ai-powered-safety-systems-at-scale-in",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-22T11:00:00.000Z",
  "source": {
    "name": "InfoQ",
    "slug": "infoq",
    "url": "https://www.infoq.com/presentations/doordash-llm-ai-moderation-platform/"
  },
  "original_language": "en",
  "account": "InfoQ presents \"SafeChat: Building AI-Powered Safety Systems at Scale in a Real-Time Marketplace\" by Bruna Pereira, a software engineer at DoorDash with over a decade of experience in software engineering. Bruna discusses how DoorDash created a hybrid moderation platform to tackle safety issues in real-time conversations. The system uses fast internal models to filter obvious cases, LLM multi-axis scoring for nuanced decisions, and no-code workflows with backtesting. Bruna explains how this architecture reduced safety incidents while scaling to millions of daily messages. DoorDash is a marketplace connecting consumers, Dashers, and merchants, with chat and voice being primary communication channels. Ensuring the safety of these interactions is crucial, with over 4 million chat messages exchanged daily. Initially, DoorDash considered using an LLM-only pipeline, but this would have been too costly and slow. Instead, they adopted a hybrid approach, starting with a fast classifier to identify obviously safe messages. When the classifier couldn't determine if a message was safe, it was passed to an LLM for further analysis. This approach significantly reduced costs and latency while maintaining high safety standards.",
  "summary": "Bruna Pereira explains how DoorDash built a content-agnostic AI moderation platform. She covers replacing costly LLM-only pipelines with a hybrid pattern: using fast internal models to filter obvious cases, LLM multi-axis scoring for nuanced decisions, and no-code workflows with backtesting. Discover how this architectural pattern cut safety incidents while scaling to millions of daily messages.…",
  "key_points": [
    "DoorDash developed hybrid moderation platform for real-time safety",
    "Fast internal models filter obvious cases, LLM for nuanced decisions",
    "Architecture reduces safety incidents while scaling to millions of messages"
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}