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

Mirriad Delivers Next-Generation Ad Tech Using AWS

Customer Company Size

SME

Region

Europe
Asia

Country

United Kingdom
China

Product

AWS Auto Scaling
Amazon EC2
AWS Trusted Advisor

Tech Stack

Python
C++
Caffe
TensorFlow

Implementation Scale

Enterprise-wide Deployment

Impact Metrics

Brand Awareness
Cost Savings
Customer Satisfaction

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

About The 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.

The 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.

The 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.

Operational Impact

Mirriad can now onboard big clients 98% faster, reducing the onboarding time from up to nine months to just a few days.
The company saves around US$100,000 a year in GPU costs due to the flexibility of AWS Auto Scaling.
Mirriad can now meet the large-scale needs of customers across regions using AWS.
The company can now architect its systems for a high level of security, isolating content for each customer to ensure none of it gets into the wrong hands.

Quantitative Benefit

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