San Diego, California
Bronze Sponsor ACL 2026
Presenting our Research Paper at ACL 2026
Multi-Agent Orchestration for Terminology-Constrained Machine Translation in Industrial Localization
Presented By Emanuele Di Rosa
DATAmundi CTO
Why this Research Matters for Global AI
Our research focuses on a multi-agent LLM pipeline that orchestrates four specialized agents across analysis, translation, post-editing, and review for terminology-constrained machine translation.
Terminology
Improves terminology consistency in production machine translation
Real-World
Designed for real world multilingual content and data pipelines.
Approach
Demonstrates multi-agent orchestration beyond single-model approaches.
See How we Support GlobalAI Teams and Researchers:
Transforming Real World Multilingual Audio into High Quality Training Data
LLM Evaluation at Scale for a Leading AI Research Organization
Evaluating AI Responses for Enterprise Search Platform
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