Customer Stories / Software & Internet
DeepBrain AI Delivers AI Studios SaaS Solution Globally with Automated Provisioning on AWS
DeepBrain AI built a fully managed deep learning pipeline on Amazon EKS, with high-volume storage on Amazon EFS. The solution means DeepBrain AI can serve more customers faster and continue to expand its business abroad.
75%
faster deployment cycles
Improved Agility
Autoscales compute and storage resources
Cutting-Edge Technology
Increases access to high-performance technologies
Reliable Video Processing
Removes bottlenecks with seamless data transfer
Global Network
Facilitates business expansion
Overview
DeepBrain AI provides user friendly text-to-video software based on deep learning technologies which are deployed to create human-like avatars capable of speaking 55 languages. As DeepBrain AI aimed to expand into new markets, it sought a rapid, high-quality, and reliable build and deployment process for its resource-intensive artificial intelligence (AI) models.
DeepBrain AI automated provisioning Kubernetes workloads with a deep learning pipeline using Amazon Elastic Kubernetes Service (Amazon EKS). It stores large volumes of images and AI models on Amazon Elastic File System (Amazon EFS) and transfers data securely between AWS and its on-premises data center with AWS DataSync. Thanks to a rapid deployment cycle, the company is able to respond quickly to customer needs and has improved service quality.
Opportunity | Improving Global Performance of AI Text-to-Video SaaS
DeepBrain AI is a tech startup, and its natural language processing software helps enterprises create interactive videos from just a script. With a library of over 100 realistic human-like avatars that can “speak” 55 languages, companies in finance, healthcare, education, and other industries can effectively reach audiences worldwide.
In addition to its flagship AI Human product, which provides face-to-face conversation with AI-powered chatbots, DeepBrain AI recently launched AI Studios. This tool empowers users to create and edit training and marketing videos in as little as 5 minutes, for as low as 20 percent of the cost of producing a video using manual tools.
Building realistic virtual avatars using deep learning technology requires a large amount of computing resources, and quick provisioning as well as autoscaling. DeepBrain AI wanted to grow AI Studios on the cloud and was considering open-source container tools such as Docker and Kubernetes. However, the company encountered limitations in these tools regarding their ability to handle high-volume, simultaneous resource demands.
Doohyun Kim, lead developer at DeepBrain AI, explains, “Our AI models use numerous images, straining network speed due to storage and processing needs. Large image sizes raised costs, slowed viewing, and caused video sync issues. Additionally, for global SaaS expansion to Europe, US, and China, a dependable high-availability network was crucial.”
Our legacy infrastructure hindered our ability to rapidly respond to fluctuating demand and changing market conditions. With high availability and autoscaling on AWS, we can address customer needs faster and provide a higher quality of service.”
Doohyun Kim
Lead Developer at DeepBrain AI
Solution | Faster Provisioning with Managed Kubernetes and AWS Storage Services
DeepBrain AI turned to Amazon Web Services (AWS) to address its performance issues and pave the way for global expansion. The company deployed Amazon Elastic Kubernetes Service (Amazon EKS) as a managed service to start, run, and scale Kubernetes workloads in AWS and its on-premises data center. “Amazon EKS made it possible for us to create a fast build and deployment environment, providing our customers with high-quality service and reliability,” Kim says.
To store its high data volumes, DeepBrain AI uses Amazon Elastic File Service (Amazon EFS), a serverless, fully managed file system built for 99.99 percent availability. Amazon EFS automatically scales up and down to handle changing workloads efficiently. DeepBrain AI also uses AWS DataSync to securely automate data movement between its data center and AWS.
Architecture
Outcome | Rapidly Responding to Changing Customer Demands
Using the latest generation of GPU computing resources available on AWS, DeepBrain AI can now perform large-scale AI model deployments in under 1 hour—a process that previously took 3–4 hours. “We achieved rapid deployment by building deep learning pipelines on Amazon EKS and Amazon EFS. The end-to-end deployment cycle is much shorter, and we’ve removed the manual burden of deployment,” Kim says.
With AWS Global Infrastructure, DeepBrain AI can reliably and securely deliver its SaaS solutions to customers abroad. Kim adds, “Our legacy infrastructure hindered our ability to rapidly respond to fluctuating demand and changing market conditions. With high availability and autoscaling on AWS, we can address customer needs faster and provide a higher quality of service.”
“As AI Studios matures,” Kim continues, “we recognize the significance of integrating advanced technologies to enhance our software solutions and drive company growth. AWS continuously tests and launches new services to benefit its customers, and we’re committed to building on AWS to leverage its latest offerings in the future.”
About DeepBrain AI
DeepBrain AI is an innovative startup that applies deep learning technologies to facilitate interactive text-to-video communication with 2D or 3D human-like avatars. Customers in industries from finance to education and health use DeepBrain AI’s products to create live chatbots and videos in minutes, at a fraction of the cost of traditional video production.
AWS Services Used
Amazon Elastic Kubernetes Service
Amazon Elastic Kubernetes Service (Amazon EKS) is a managed Kubernetes service to run Kubernetes in the AWS cloud and on-premises data centers.
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Amazon Elastic File System
Amazon Elastic File System (EFS) automatically grows and shrinks as you add and remove files with no need for management or provisioning.
AWS DataSync
AWS DataSync is a secure, online service that automates and accelerates moving data between on premises and AWS Storage services.
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