Laerdal Medical transforms training with Azure AI Text-to-Speech
Laerdal Medical enhanced the quality and accessibility of its training simulations by seamlessly integrating Microsoft Azure AI's Text-to-Speech technology. This advancement significantly reduced the time required to develop personalized voice content, accelerating content creation from months to hours. The implementation enables Laerdal to design diverse, inclusive scenarios aligned with its mission to save lives, targeting healthcare training needs efficiently.
- Organization
- Laerdal Medical
- Industry
- Healthcare
- Location
- Norway
- Published
- May 2025
Reported outcomes
Strategic outcomes
Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks
- Customer
- Laerdal Medical
- Provider
- Microsoft
- Maturity
- Unknown
- Linked source
- Microsoft Customers Page
No explicit deployment-stage evidence found.
Primary read
Use case focus
Showing 2 of 2
- 1Medical training simulation
- 2Voice customization
- Time-intensive process to develop custom voiceovers for simulations.
- Limited personalization options in training scenarios.
- Increasing need for diverse and adaptable training content.
- Integrating Azure Text-to-Speech for quick content production.
- Automating the voice creation process for seamless deployment.
- Enhancing inclusivity through customizable voice scenarios.
- Reduced voice production time from months to hours.
- Enriched healthcare simulations with adaptable scenarios.
- Advanced the goal of training for saving lives by 2030.
Architecture
Azure Text-to-Speech automates voice customization, enabling scalable, inclusive training simulations.
Sources & evidence1
- Customer explicitly identified
- Primary source available
- Technical implementation details available
- Recent evidence check available
- Last evidence check: Jul 22, 2026.
The cited source is no longer reachable and the organization has no newer case. Not a claim the system was discontinued.
- Cited source last checked Jun 12, 2026 — broken (1/1 broken).
Measures whether this deployment's public evidence persists — not whether the system is still in production.
AI-generated summary. Verify important details with the linked sources before relying on this case.
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