As published on labelbox.com. Captured by usedby on Oct 7, 2026.
What happened
Edelman's Data & Intelligence team uses Labelbox to produce training data for proprietary models that score consumer trust in brands from web text. The process includes selecting contributors, incorporating internal domain-expert feedback, and assessing data quality, with the Python SDK connected to its AWS data lake.
Summary written by usedby from the source page, in English. The figures are those of Labelbox and Edelman, not ours.
The key step was folding in internal domain experts who carry institutional knowledge of brand trust, answering questions like “what indicates trust?” and “how do you spot a crisis?” to refine the signal.
one of the most important components is around domain expertise. Expert feedback is expensive. It's less expensive than it used to be thanks to services like Labelbox, but it’s still a time intensive process, so we first need to incorporate the domain expertise that we have across our business and our clients and then pull that into ML projects.
What the story claims, and what we checked
We compared the story with its live page on Oct 7, 2026.
- The passage quoted aboveCheckedCopied word for word from the page, near the name of Edelman.
- Edelman uses LabelboxCheckedConfirmed line. Latest check across sources: Oct 7, 2026.
- The result itselfNot checkedWe quote it; we did not measure it.




