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Mirriad Delivers Next-Generation Ad Tech Using AWS
Technology Category
- Analytics & Modeling - Computer Vision Software
- Analytics & Modeling - Machine Learning
- Infrastructure as a Service (IaaS) - Cloud Computing
Applicable Industries
- Automotive
Applicable Functions
- Business Operation
- Sales & Marketing
Use Cases
- Computer Vision
- In-process Traceability
Services
- Cloud Planning, Design & Implementation Services
- Data Science Services
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.
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 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
Quantitative Benefit
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