Amazon Web Services Case Studies Mirriad Delivers Next-Generation Ad Tech Using AWS

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	Mirriad Delivers Next-Generation Ad Tech Using AWS Amazon Web Services

Mirriad Delivers Next-Generation Ad Tech Using AWS

Amazon Web Services

Technology Category	Analytics & Modeling - Machine Learning Infrastructure as a Service (IaaS) - Cloud Computing Analytics & Modeling - Computer Vision Software
Applicable Industries	Automotive
Applicable Functions	Sales & Marketing Business Operation
Use Cases	Computer Vision In-process Traceability
Services	Cloud Planning, Design & Implementation Services Data Science Services
Challenge	Mirriad, a London-based company, delivers next-generation advertising solutions by using its computer vision technology to naturally place brands in premium video content across TV, online, and mobile channels. The challenge for Mirriad was achieving this intelligent insertion of ads at scale. The company was initially using physical data centers, which proved to be a bottleneck when it came to onboarding big businesses. In addition to fast access to compute capacity, another vital requirement for the company was the ability to use NVIDIA GPUs across multiple regions worldwide. Read More
About Customer	Mirriad is a video technology company based in London that delivers in-video advertising to customers around the world. The company uses machine learning techniques to naturally blend brand advertising into popular entertainment content. Mirriad's technology supports in-video advertising, allowing brands to be placed in premium video content across TV, online, and mobile channels. The company's Chief Technology Officer, Tim Harris, explains that they achieve this by employing machine learning techniques that focus on annotating video metadata so they can pick the right piece of content for the right brand. Read More
Solution	Mirriad transitioned to Amazon Web Services (AWS), a process that took around a year. This transition instantly solved their capacity challenges and enabled them to set up customers 98% faster. The company uses AWS Auto Scaling across Amazon Elastic Compute Cloud (Amazon EC2) G2 and G3 instances for all of its video processing. This allows them to use between 20 and 40 GPU nodes for a typical production workload, which lasts around 15 to 20 minutes. The company also uses AWS Trusted Advisor to maintain and prove compliance, ensuring that their systems stand up to vigorous security audits. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Infrastructure as a Service (IaaS) - Cloud Computing

Analytics & Modeling - Computer Vision Software

Applicable Industries

Automotive

Applicable Functions

Sales & Marketing

Business Operation

Use Cases

Computer Vision

In-process Traceability

Services

Cloud Planning, Design & Implementation Services

Data Science Services

Challenge

Mirriad, a London-based company, delivers next-generation advertising solutions by using its computer vision technology to naturally place brands in premium video content across TV, online, and mobile channels. The challenge for Mirriad was achieving this intelligent insertion of ads at scale. The company was initially using physical data centers, which proved to be a bottleneck when it came to onboarding big businesses. In addition to fast access to compute capacity, another vital requirement for the company was the ability to use NVIDIA GPUs across multiple regions worldwide.

About Customer

Mirriad is a video technology company based in London that delivers in-video advertising to customers around the world. The company uses machine learning techniques to naturally blend brand advertising into popular entertainment content. Mirriad's technology supports in-video advertising, allowing brands to be placed in premium video content across TV, online, and mobile channels. The company's Chief Technology Officer, Tim Harris, explains that they achieve this by employing machine learning techniques that focus on annotating video metadata so they can pick the right piece of content for the right brand.

Solution

Mirriad transitioned to Amazon Web Services (AWS), a process that took around a year. This transition instantly solved their capacity challenges and enabled them to set up customers 98% faster. The company uses AWS Auto Scaling across Amazon Elastic Compute Cloud (Amazon EC2) G2 and G3 instances for all of its video processing. This allows them to use between 20 and 40 GPU nodes for a typical production workload, which lasts around 15 to 20 minutes. The company also uses AWS Trusted Advisor to maintain and prove compliance, ensuring that their systems stand up to vigorous security audits.

Impact #1	Mirriad can now onboard big clients 98% faster, reducing the onboarding time from up to nine months to just a few days.
Impact #2	The company saves around US$100,000 a year in GPU costs due to the flexibility of AWS Auto Scaling.
Impact #3	Mirriad can now meet the large-scale needs of customers across regions using AWS.

Impact #1

Mirriad can now onboard big clients 98% faster, reducing the onboarding time from up to nine months to just a few days.

Impact #2

The company saves around US$100,000 a year in GPU costs due to the flexibility of AWS Auto Scaling.

Impact #3

Mirriad can now meet the large-scale needs of customers across regions using AWS.

Benefit #1	98% faster onboarding of clients.
Benefit #2	US$100,000 savings a year in GPU costs.
Benefit #3	Successful large-scale campaigns resulting in nearly 800 million ad impressions and 58% brand awareness, up 17 percentage points.

Benefit #1

98% faster onboarding of clients.

Benefit #2

US$100,000 savings a year in GPU costs.

Benefit #3

Successful large-scale campaigns resulting in nearly 800 million ad impressions and 58% brand awareness, up 17 percentage points.

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Overview

Mirriad Delivers Next-Generation Ad Tech Using AWS

Operational Impact

Quantitative Benefit