Glean
AI / ML EngineerStrategicAug 6, 2026

Prioritize multilingual retrieval quality measurement

A shared language does not guarantee a shared path to knowledge.

Weak feedback can make query understanding, retrieval coverage, and answer usefulness look like the same problem.

Our regional teams shouldn’t have to translate the company before they can search it.

Alireza Zayed · Global IT Operations Director

Oversees knowledge access for regional teams that work across English, Japanese, and Spanish systems.

What pulls against what

  • global coverage vs. depth in priority cohorts
  • behavioral proxies vs. real task success
  • standard benchmarks vs. enterprise workflow validity
  • fast directional evidence vs. durable measurement

What is at stake

The evidence supports several explanations for uneven multilingual success. A reversible experiment must reveal the right optimization target before resources harden around the wrong one

Why Glean

At Glean, this can matter when global teams rely on knowledge created in different languages and tools.

Written for

research-minded ML engineermultilingual retrieval specialistexperimentalist

This is the setup. The work is inside.

Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.