Streamlining Workflows with AI – MosAIQ Case Study

Supporting a Leading Restaurant Management Platform with Scalable Multilingual Content

The Challenge

A cloud-based restaurant management software company faced the challenge of scaling multilingual marketing content across global markets without compromising quality or increasing costs. With over 400 blog articles to process in Q4 2024 and continuous content creation planned for 2025–2026, the need for a hybrid AI-human localization workflow became urgent. They needed a system capable of handling high-volume, high speed translations while maintaining brand voice and SEO performance.

Key workflows included:

• Blog localization (400+ articles, 300k words, 5 weeks turnaround, 30% cost savings)
• Hyper-localization (63 articles, 315k words, 15 days, 60% faster turnaround, 50% cost savings)
• Exploratory AI content creation (10 articles/week, 80% potential cost savings vs. copywriters)

Case Study

Multilingual expansion. The client wanted to expand marketing pages into Spanish and Chinese for the US.

Challenges:

• Backlog of blog articles
• The volume of marketing for the local US market ballooning

How to localize at scale without cutting corners

• Like everyone else, the company was asking itself if there was a way to catch up.
• Traditional translation cycles take too long and are expensive.
• Was there a hybrid AI solution mature enough to suit their needs without sacrificing quality?

The Solution

Argos implemented the MosAIQ platform – a hybrid NMT + LLM approach that combines automation, AI quality estimation, and human-in-the-loop review. The workflow included TM cleanup, machine translation or LLM-based translation, automatic post-editing, and AI-powered MQM quality evaluation. Projects were managed through Phrase TMS, enabling seamless collaboration between client’s CMS, Argos linguists, and AI agents.

The Result

The MosAIQ workflow enabled the company to scale multilingual content efficiently while maintaining quality and brand alignment. Dynamic prompting and AI LQA ensured that machine-generated translations met enterprise-grade quality standards. As a result, the client achieved up to 60% faster turnaround times and 50% average cost reduction while laying the foundation for future AI-driven multilingual marketing initiatives.

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