Google Cloud Platform Case Studies Affable's Success with Google Cloud: Processing 100 Million Events Daily

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	Affable's Success with Google Cloud: Processing 100 Million Events Daily Google Cloud Platform

Affable's Success with Google Cloud: Processing 100 Million Events Daily

Google Cloud Platform

Technology Category	Analytics & Modeling - Machine Learning Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries	Education Equipment & Machinery
Applicable Functions	Logistics & Transportation Product Research & Development
Use Cases	Clinical Image Analysis Predictive Maintenance
Services	Cloud Planning, Design & Implementation Services Data Science Services
Challenge	Affable, a Singapore-based startup, has built an AI-based influencer marketing platform that tracks over 1 million micro-influencers across various social media platforms. The company's challenge was to process vast amounts of data and images to recommend key micro-influencers to clients for promoting their products and services. The business was processing 100 million events through its data pipelines and using machine learning models to serve up to 20 million image requests per day. The agility and responsiveness were critical to the success of the business. However, the company was struggling with the fast delivery of accurate, actionable influencer data to meet client demands. The company initially started running its platform on a traditional cloud service, but soon saw an opportunity to use machine learning and big data analysis to create even more value for its clients. Read More
About Customer	Affable is a Singapore-based startup that has developed an AI-based influencer marketing platform. The company tracks over 1 million micro-influencers across various social media platforms such as Facebook, YouTube, Instagram, and others. Its platform provides curated lists of relevant influencers to clients, complete with demographics, interests, and brand partnerships of followers. These lists are generated through machine learning, which also allows the business to detect fake followers. Founded in October 2017, Affable enables brands and marketers to discover, measure, and engage social media micro-influencers, presenting opportunities to promote products and services. Read More
Solution	Affable evaluated Google Cloud and found the platform to be the easiest to use. Google Cloud offered compelling machine learning and big data processing, management, and analysis services. It was also more developer-friendly, allowing the team to get started and complete work faster. The platform was scalable and incorporated a range of managed services, enabling Affable to execute its strategy of focusing its developers and data scientists on delivering value. Affable finalized its Google Cloud deployment in April 2019 as use of its platform began to surge. The Google Cloud architecture comprised AI Platform, BigQuery, Cloud SQL, and Pub/Sub. With these tools, Affable was able to build a recommendation engine that identifies the influencers most compatible with clients’ needs in just two weeks. Pub/Sub acted as the data-streaming backbone that funneled data to the engine from various sources. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Platform as a Service (PaaS) - Application Development Platforms

Applicable Industries

Education

Equipment & Machinery

Applicable Functions

Logistics & Transportation

Product Research & Development

Use Cases

Clinical Image Analysis

Predictive Maintenance

Services

Cloud Planning, Design & Implementation Services

Data Science Services

Challenge

Affable, a Singapore-based startup, has built an AI-based influencer marketing platform that tracks over 1 million micro-influencers across various social media platforms. The company's challenge was to process vast amounts of data and images to recommend key micro-influencers to clients for promoting their products and services. The business was processing 100 million events through its data pipelines and using machine learning models to serve up to 20 million image requests per day. The agility and responsiveness were critical to the success of the business. However, the company was struggling with the fast delivery of accurate, actionable influencer data to meet client demands. The company initially started running its platform on a traditional cloud service, but soon saw an opportunity to use machine learning and big data analysis to create even more value for its clients.

About Customer

Affable is a Singapore-based startup that has developed an AI-based influencer marketing platform. The company tracks over 1 million micro-influencers across various social media platforms such as Facebook, YouTube, Instagram, and others. Its platform provides curated lists of relevant influencers to clients, complete with demographics, interests, and brand partnerships of followers. These lists are generated through machine learning, which also allows the business to detect fake followers. Founded in October 2017, Affable enables brands and marketers to discover, measure, and engage social media micro-influencers, presenting opportunities to promote products and services.

Solution

Affable evaluated Google Cloud and found the platform to be the easiest to use. Google Cloud offered compelling machine learning and big data processing, management, and analysis services. It was also more developer-friendly, allowing the team to get started and complete work faster. The platform was scalable and incorporated a range of managed services, enabling Affable to execute its strategy of focusing its developers and data scientists on delivering value. Affable finalized its Google Cloud deployment in April 2019 as use of its platform began to surge. The Google Cloud architecture comprised AI Platform, BigQuery, Cloud SQL, and Pub/Sub. With these tools, Affable was able to build a recommendation engine that identifies the influencers most compatible with clients’ needs in just two weeks. Pub/Sub acted as the data-streaming backbone that funneled data to the engine from various sources.

Impact #1	The use of Google Cloud has significantly improved Affable's operational efficiency. The platform's ease of use and highly functional services have enabled the company to build a recommendation engine in just two weeks. The company is now able to serve up to 20 million requests per day using AI Platform. The platform helps understand the images in photos, identify items, and use these to help determine the categories to assign influencers to. The company has set up pipelines and trained models so they can do the job of 1,000 human beings who would otherwise be working to annotate, categorize, and explain each image. This has significantly reduced the need for human intervention, thereby saving time and resources.

Impact #1

The use of Google Cloud has significantly improved Affable's operational efficiency. The platform's ease of use and highly functional services have enabled the company to build a recommendation engine in just two weeks. The company is now able to serve up to 20 million requests per day using AI Platform. The platform helps understand the images in photos, identify items, and use these to help determine the categories to assign influencers to. The company has set up pipelines and trained models so they can do the job of 1,000 human beings who would otherwise be working to annotate, categorize, and explain each image. This has significantly reduced the need for human intervention, thereby saving time and resources.

Benefit #1	Saves 20 hours of development productivity per engineer per month
Benefit #2	Delivers projects 40% faster than if using other cloud services
Benefit #3	Creates recommendation engine in just two weeks

Benefit #1

Saves 20 hours of development productivity per engineer per month

Benefit #2

Delivers projects 40% faster than if using other cloud services

Benefit #3

Creates recommendation engine in just two weeks

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Overview

Affable's Success with Google Cloud: Processing 100 Million Events Daily

Operational Impact

Quantitative Benefit