Machine Learning
Meta

Machine Learning Driven Search Enhancement

Sector:
Social Media
Our Role:
Custom Development for AI-based Search Solution
Outcome:
5x improvement in search capabilities across Meta's massive supplier network

They know a lot about the products they build on and were very responsive. Their project manager broke down barriers and explained all the intricacies of the custom software development effort in a way that was easy to understand.

Jason Trimiew
Group Head
Challenge
  • Facebook approached Azumo with a need to improve its search capability for diverse suppliers within the Facebook supplier ecosystem. 
  • They have over 3.5 million suppliers in their database, making it difficult for their Supplier Diversity team to find the right supplier for Facebook's needs.
  • This project was an extension of the application we built for them to track and manage Supplier information at their global conferences.

solution
  • Azumo built a custom service called AIML. This included NER (named entity recognition) to extract supplier capabilities, products using a Natural Language Understanding (NLU) library. 
  • AIML Service seeks to process both capabilities and products /services that each Supplier offers. 
  • The service will label the outputs where possible and an entry will show up for each instance in which capabilities or products / services appear.
  • The output provides information at the company level and at the product/ service level that Facebook can use to improve their search capability.

benefits
  • With a team of 5 engineers, a PM, and an Architect, Azumo was able to build the PoC that would identify and extract Supplier capabilities and  product/ services from the provided text. 
  • We used OCR technology to extract the text. 
  • Today Facebook can find suppliers quickly and connect with ease.
  • Agile development approach produced an enterprise-ready solution in eight (8) weeks.

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