{
  "id": 1499900,
  "title": "How Heidi built production-ready AI for healthcare at global scale",
  "url": "https://urgent.news/2026/08/17/how-heidi-built-production-ready-ai-for-healthcare-at-global-scale",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-17T14:30:00.000Z",
  "source": {
    "name": "VentureBeat",
    "slug": "venturebeat",
    "url": "https://venturebeat.com/data/how-heidi-built-production-ready-ai-for-healthcare-at-global-scale"
  },
  "original_language": "en",
  "account": "Heidi, an Australian-founded AI Care Partner, has successfully built production-ready AI for healthcare on a global scale. Its flagship product, Heidi Scribe, automates administrative work for clinicians across more than 190 countries, handling roughly 2.7 million patient interactions per week. The company's success lies in its architectural decisions made years before reaching global scale, with data residency and auditability built into every aspect of the system. Liu, co-founder and chief technology officer, explains that regulatory compliance varies by region, so patient data must live in-region, enforced by architecture. Heidi runs fully logically isolated production deployments worldwide, with auditability built in to answer model inputs, outputs, and clinician changes. Choosing a database for AI workflows, Heidi opted for a document database to handle diverse medical data, consolidating it into a consistent format and location to connect seamlessly with AI. MongoDB was the natural choice due to its flexibility and ability to accommodate rapidly changing AI data without reshaping the underlying database. MongoDB Atlas was selected for its AI-ready features, including MongoDB Vector Search, which allows Heidi to handle diverse medical data and retrieve from licensed clinical knowledge bases while remaining jurisdiction-aware. This results in a trustworthy clinical Retrieval-Augmented Generation (RAG) system, with evidence retrieving from licensed clinical knowledge bases and living in the same regionally isolated deployments as the rest of the data, ensuring compliance and scale.",
  "summary": "Presented by MongoDB Building AI that is accurate, secure, and reliable is a major engineering feat for organizations subject to the compliance obligations that govern healthcare, financial services, and transportation. The challenge of delivering AI-driven products is compounded by the fact that technology in these industries has tended to lag behind other sectors because regulation requires…",
  "key_points": [],
  "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."
}