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.
More of our Work
Tool and strategies modern teams need to help their companies grow.
