ecommerce_ops · ecommerce · workflow
OLX uses Prosus AI Assistant to extract and normalize job roles from job ad titles and descriptions
OLX lacked clearly defined job roles within its jobs taxonomies, with roles buried in ad titles and descriptions, creating a barrier to efficient and organized search for job-seekers.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Build job-role taxonomy tree
Prosus AI Assistant generates a hierarchical job-role taxonomy from top-searched keywords and sampled job roles per category.
Tools used
Prosus AI AssistantLangChain
Outcome
The A/B test showed positive uplift in most Successful Events metrics and a significant decrease in search extensions and keyword searches per user in the low-result segment, though some impact metrics had small effect sizes and not all reached statistical significance. Operating cost was approximately 15K per month, prompting consideration of self-hosted alternatives.
Results
Volume60%
Cost replacedapproximately 15K per month
Running sinceJuly 2023
Source
https://tech.olx.com/extracting-job-roles-in-job-ads-a-journey-with-generative-ai-e8b8cf399659
Grounding & classification
Source type: technical build writeup
27 fields verified against source quotes.
content generationdata extractiondocument classificationform submissionmetric backednamed customerproduction runtime claimedtools describedworkflow describedecommerceaccuracy improvementcycle time reductiontechnical build writeupdata entry opsecommerce opsdocument to recordextract classify route