FOR AI, PRODUCT, AND LOCALIZATION TEAMS
Multilingual AI to Power Accurate Model Evaluation
Measure, validate, and improve multilingual model quality with domain-expert evaluation, human-in-the-loop review, and benchmark creation, delivering trustworthy, repeatable results across 100+ languages.
The Lilt Difference
Human + AI Evaluation Pipelines
Combine automated scoring with optional expert human review to validate precision, recall, contextual accuracy, and fluency across multilingual outputs.
Cross-Lingual Consistency Testing
Run evaluations that measure linguistic consistency, relevance, and tone across languages, domains, and modalities—not just synthetic benchmarks.
Continuous Quality Feedback Loops
Feed error analysis and evaluation signals directly back into model workflows to improve robustness, reduce failure rates, and strengthen outputs over time.
Flexible, KPI-Aligned Metrics
Measure what matters with customizable evaluation criteria—such as fluency, relevance, factual accuracy, and bias reduction—mapped to your internal quality standards.
Use Cases
Model Benchmarking and Comparison
Compare models side-by-side using multilingual benchmarks to evaluate accuracy, relevance, and consistency across languages and domains.
Human-in-the-Loop Review
Layer expert linguistic evaluation on top of automated scoring for outputs that require cultural accuracy, domain precision, or stylistic alignment.
Continuous Model Improvement
Feed multilingual evaluation data back into fine-tuning or RLHF workflows to iteratively improve model performance.
Localization Quality Assessment
Evaluate fluency, fidelity, and production-readiness based on real content—not BLEU-style metrics that miss nuance, meaning, and intent.
Risk and Error Analysis
Identify systemic weaknesses by language or content type and reduce deployment risk through targeted remediation before release.
Frequently Asked Questions
What is the best way to get fast, accurate translation for my enterprise?
The best approach is using an enterprise-grade multilingual AI and translation platform like LILT which combines adaptive AI with human-expert verification to handle both speed and quality needs across your organization.
Why shouldn't I rely on free or basic machine translation tools for my business?
Basic machine translation lacks the necessary security, compliance, and domain-specific context required for enterprise and regulated content, leading to potential inaccuracies, inconsistent brand voice, and major risk for high-stakes content.
How can a single platform manage all my content types, from marketing to technical docs?
An advanced platform uses workflow connectors and contextual AI to integrate directly with your content systems (like CMS, PLM, and code repositories), allowing you to seamlessly translate everything from UI strings and documents to video and audio in over 100 languages.
When should I choose human-verified translation over instant machine translation?
Select human-verified translation for high-stakes content that requires the highest quality, such as legal documents, financial disclosures, regulatory filings, and mission-critical marketing materials, as this minimizes compliance risk and ensures brand integrity.