Building brand-aware global websites: LILT’s enterprise AI strategy

In this edition of our Going Global series, we’re excited to spotlight how LILT helps brands deliver seamless multilingual experiences on Webflow. From strategic localization workflows to real-world customer wins, you’ll learn how global-ready design meets powerful translation management.

Webflow revolutionized the enterprise marketing stack. It empowers marketing teams to build sophisticated, high-performance sites without waiting on engineering backlogs, allowing brands to move at the speed of culture. However, for many growing brands, this agility hits a wall when content needs to cross borders. 

Traditional localization is often manual, spreadsheet-heavy, and fundamentally incompatible with the pace of modern digital marketing. When you are accustomed to a no-code environment, dragging CSV files to translation agencies creates a bottleneck that stalls your go-to-market speed. 

Yet, relying on generic, unverified machine translation can be a liability. Generic models lack the nuance to reflect your unique brand voice. If your French landing page reads like every other company, or your German headline misses a specific cultural hook, you haven't just failed a language check. You've broken the trust that drives revenue.   

LILT solves this creator trade-off. 

As the complete AI solution for enterprise-grade translation and localization, LILT brings brand-aware AI, agentic workflows, and a network of domain-expert linguists directly into your Webflow environment. It allows you to deploy an AI-first global strategy with the same precision you apply to your design. LILT is a strategic partner that enables you to scale your local presence as fast as your global growth goals demand.

Custom AI in your brand voice

For global brands, consistency is the foundation of trust. With widespread adoption of generic AI, there is a risk of “brand identity drift.” Generic Large Language Models (LLMs) use terms that are grammatically correct but may be tonally wrong for your brand. 

LILT solves this by training the AI on your company’s unique data. Whether you use one of LILT’s proprietary models or a third-party LLM like Gemini or GPT-4, LILT customizes that core technology with your specific enterprise context (e.g., historical data, glossaries, and style guides) and real-time translator feedback. 

Real-time customization

When you send a Collection or a page for translation via the LILT <> Webflow Connector, your unique AI mode generates an initial translation informed by your brand history and preferences. As verified expert linguists review translation segments, their updates fuel real-time model adaptation. 

For example, if a linguist changes a literal translation of "Shipping" to "Delivery" in Spanish to better match your brand, that preference will automatically be saved as training data. The model adapts immediately for the rest of the page and future projects.

Context-specific AI models

For complex enterprise needs, LILT allows you to manage distinct models for different content types within Webflow. Enterprises aren't just building a multilingual web experience. They are building a library of proprietary AI models that understand their business better than any off-the-shelf tool:

• Model A is trained for high-precision, compliant legal text for your Terms and Conditions pages
• Model B is trained for high-volume, instructional text for your knowledge base. 
• Model C is trained for high-impact, persuasive copy on your home page. 

By grounding your AI model in your unique data, LILT ensures it evolves alongside your content strategy. LILT’s fine-tuned models delivered 15% greater accuracy for a global tech giant’s e-commerce translation compared to unadapted, off-the-shelf AI. This enhanced precision ensures that every page and piece of SEO metadata is crafted to resonate deeply with the local audience, allowing you to bypass extensive edits and maintain your team’s go-to-market velocity.

With LILT, this global brand can maintain high-fidelity brand voice while scaling content at the speed of its product cycles.