TEALBOOK nobody ’ s going to think about the problem this way and then it will be a decade or two later and it will still be high software dependency with siloed and disparate data . And I just didn ’ t think that was acceptable .”
Stephany and her team at TealBook pioneered a machine learning-driven approach to data curation , ensuring businesses have access to accurate and up-to-date information . “ The thesis is that suppliers are more likely to update their websites before they update a bunch of supplier portals ,” Stephany explains . “ If we could capture the name , address , goods and services , team structure , any sort of logo of certificates or customers and any sub-site that would link us to other companies , then we could probably get a pretty good picture of what that company does .”
This led to the creation of universal supplier profiles , upon which TealBook expanded the data foundation .
“ That was pretty novel at the time ,” Stephany adds . “ We could automate the collection , verification , and the enrichment of supplier data , create our own profiles and we didn ’ t need to depend on D & B or other sources .” And so , TealBook became an AIfirst company that used automation
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