LILT

LILT runs multilingual content programs for organizations where a bad translation carries real cost — regulatory submissions, clinical trial documentation, defense and public-sector messaging, product launches, and support content in dozens of languages. The pitch is consolidation: instead of a translation management system plus a stack of language service vendors plus whatever your marketing team runs through a chatbot on the side, LILT puts contextual models, agentic workflows, human reviewers, connectors, and budget controls in one governed platform. The pieces that matter in practice are Assist, which uses AI agents to push work through review and localization pipelines with less manual triage, and Verify, which routes output to subject-matter experts — either LILT's network or your own reviewers — when accuracy and audit trails are non-negotiable. Models are context-aware and self-learning, sharpening with each human correction, and you can run LILT's proprietary models alongside third-party LLMs rather than betting the program on one vendor. Governance is where LILT separates itself from cheaper tooling: real-time visibility into model use, data use, and brand consistency, plus SOC 2 Type II, ISO 9001, and ISO 17100 certifications and private, on-prem, or air-gapped deployment for data-residency requirements. The company also sells to AI builders. GAIA-v2-LILT, announced in August 2026, is a re-audited multilingual extension of the GAIA agent benchmark covering Arabic, German, Hindi, Korean, and Portuguese, and it found that translation artifacts can shift model performance by up to 20% — a number that should bother anyone shipping multilingual agents. Named customers include Intel, Lenovo, Canva, and the U.S. National Weather Service, which is a reasonable proxy for the buyer profile: large, multilingual, and under some form of compliance pressure. It is not a self-serve translator, and the pricing page asks you to talk to sales. If you want to paste text