In a move to capture the growing US-Spanish market, car-sharing giant Turo leveraged Crowdin’s AI orchestration and cut time-to-market by 90%.
Turo, the world’s leading peer-to-peer car-sharing marketplace, has reached a $1B valuation by leaning into a “trust-first” model. To maintain that trust across borders, Gideon Hod, Director of Product Operations, identified a critical need: moving away from slow, manual localization cycles toward a high-velocity, automated ecosystem.
Challenge: Velocity vs. Volume
Turo’s expansion into France highlighted a common industry bottleneck. Despite having existing French Canadian assets, adapting them for Europe required slow manual coordination.
When data revealed that thousands of US users were already accessing the app with Spanish-set devices, Turo knew they couldn’t wait 3-4 months – the traditional turnaround for a full ecosystem localization.
Strategy: Orchestrated Automation
Rather than a traditional linear hand-off, Turo implemented an AI-integrated workflow within Crowdin. The goal was to automate the localization process while keeping human expertise in the loop for quality assurance.
Turo’s localization stack within Crowdin:
- Translation Memory (TM) First: Ensuring 100% consistency with previous brand-approved content.
- AI Orchestration: New strings are processed by LLMs (OpenAI and Anthropic) using highly specific prompts that define Turo’s “personable and concise” brand voice.
- AI-Proofreading: A secondary AI agent reviews the output against the glossary and persona guidelines.
- Human Review: If AI confidence scores are low or technical complexity is high, strings are routed to human experts.
Results: 98% cost reduction for translations
By shifting the bulk of the translation work to an AI-first workflow, Turo achieved unprecedented metrics:
- Time-to-Market: Reduced from months to just one week for a full-ecosystem Spanish launch (iOS, Android, and Web).
- Cost Efficiency: By using AI translation in Crowdin, Turo achieved a ~98% reduction in production costs compared to traditional per-word rates.
- Operational Scale: The “fallback rate” to human review has plummeted, allowing the internal team and their agency partners to focus only on the most linguistically nuanced or high-visibility content.
Product Ops Perspective
For Gideon Hod, the project’s success shows the importance of Product Operations in the localization cycle. By treating localization as a feedback loop rather than a translation task, Turo committed to adding more languages in the coming months.
Read the original case study 98% Cheaper, 90% Faster: Turo’s AI Localization with Crowdin.