If you're using a screen reader or you're a large language model, follow this link to an experience that's optimized for you

    LILT Workflows: Designing Configurable Translation Processes

    Enterprise UX
    Workflow Design
    System Architecture
    User Research
    AI Integration
    LILT Workflows interface design

    Role

    Principal Designer

    Team

    1 Designer (me), 1 PM, 3-4 Engineers, 1 QA

    Collaborated with

    Engineering
    Product
    Customer Success
    Linguists
    Production Managers
    Enterprise Customers
    ⚙️

    TL;DR

    Designed smart workflow templates reducing enterprise setup time by 75% through 4 predefined patterns covering 80%+ of use cases—unlocking enterprise deals without overwhelming complexity.

    Challenge & solution

    LILT's simple "Translate → Review → Done" worked for most customers, but enterprises needed AI quality checks, file preprocessing, and additional review stages. Add complexity without breaking simplicity.

    Competitor workflow builders were overly complex. Predefined templates could serve 80%+ of enterprise needs while maintaining ease of use.

    • Smart template system with Translate, Review, AI Review, and file processing steps
    • 75% reduction in setup time, improved enterprise satisfaction, enabled new market segments
    • Process: cross-role research, competitive analysis, template architecture, customer validation

    Design process & key decisions

    Research & pattern discovery

    25+ interviews revealed predictable workflow patterns—most complexity came from specific steps (AI review, file processing), not endless customization. Competitive analysis showed overwhelming workflow builders that confused 80%+ of users, so I focused on the real 'why': serving 80%+ of enterprise needs without overwhelming complexity.

    Template architecture

    Created 4-5 predefined workflows covering 80%+ of use cases: Simple Translation, Translation + Review, Translation + AI Review + Human Review. Added file processing for complex formats.

    AI integration

    Designed AI Review steps with seamless handoffs between automated and human stages. Enabled hybrid workflows combining AI preprocessing, human translation, AI review, and final approval.

    Enterprise validation

    Template workshops with key customers validated the approach. Ensured compliance requirements and audit trails for regulated industries.

    Cross-role alignment

    Gathered input from linguists, PMs, and enterprise customers to ensure workflows met real-world needs—the collective wisdom of diverse stakeholders shaped the template approach.

    Results & user feedback

    • Template-first success: eliminated decision paralysis, served 80%+ of users without customization
    • AI positioning: adding AI review positioned LILT ahead in quality assurance
    • Enterprise unlock: complex file format support through templates enabled major deals

    Some edge cases still needed more customization than templates provided, requiring careful balance between simplicity and flexibility.

    Broader impact

    The template-first approach to workflows created a design philosophy applied across LILT's enterprise features:

    80/20 rule in practice

    Competitive analysis showed that 80%+ of users needed the same 4-5 patterns—serving the majority well beats serving everyone poorly.

    Smart defaults over complexity

    Well-designed templates eliminate decision paralysis while still accommodating edge cases through progressive disclosure.

    AI as workflow step

    Integrating AI review as a workflow step demonstrated that enterprise AI features need thoughtful UX to build trust—not just capabilities.

    Complexity can be simple

    Enterprise features succeed when they feel powerful but not overwhelming—template-based system patterns now apply across LILT's tooling.

    Key learnings

    Templates beat builders

    Predefined templates covering 80%+ of use cases provide better UX than endless customization options.

    Competitive analysis shows what not to build

    Competitor workflow builders proved that complexity doesn't equal value for user experience.

    AI needs thoughtful UX

    Adding AI as a workflow step requires careful design to maintain user trust and efficiency.

    Customer validation prevents over-engineering

    Direct workshops revealed simple templates solved enterprise needs better than complex systems.

    Enterprise features succeed when they feel powerful but not overwhelming—smart defaults often serve users better than endless options.

    Building enterprise-grade process management?

    Get in touch