Automotive


Sports Car Manufacturer

Short to the story


Established sports car manufacturer collaborated with Grape Up on designing a solution allowing its internal AI, ML, and Data Science teams to accelerate the process of creating and productionizing AI applications.


Challenge


  • Allowing software development teams to develop AI &ML services and bring them into production fast

Approach


  • Designing reliable and extensible architecture, capable of handling hundreds of accounts for the platform

Goal


  • Building an environment allowing for agile development of production-ready AI applications

Outcome


  • Robust, reliable ML infrastructure supporting productionizing of AI/ML algorithms and workloads

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Challenge



Simplifying the process of building production-ready AI services and reducing time for resource management


While the automotive industry is rapidly changing by adopting a software-first strategy, like in other sectors, automotive enterprises struggle with productionizing AI and ML R&D projects. Machine Learning and Data Science teams face numerous challenges, including determining the proper technology, automating workflows, managing computing resources, managing data, and building solutions meeting internal regulations. All these issues can complicate the project even before the kick-off.

One of the leading sports car manufacturers decided to support its AI teams by providing them with a dedicated deployment platform. The company was determined to address common challenges and empower ML engineers and Data Scientists to focus on creating and bringing to production AI algorithms.



Approach



Building AI and ML deployment platform using proven cloud-native technologies


The Grape Up team joined the project to design reliable and extensible architecture, capable of handling hundreds of client accounts for the platform, as well as pick the best tools and technologies ensuring scalability and resilience.

Along with building the platform architecture leveraging Terraform orchestrating Cloud Formation scripts, Grape Up ensured efficient migration of existing environments. The solution was integrated with Continuous Integration pipelines and the E2E tests set. The platform is hosted in the AWS cloud, taking benefits from high performance across multiple regions around the globe.



Goal




Accelerating productionizing of AI and ML applications



Simplifying access to data and computing resources



Providing easy and quick project and user onboarding



Ensuring high scalability supporting 100+ accounts and projects





Outcome



Ensuring fast and efficient productionizing of AI/ML software by providing resilient deployment platform


Delivered AI Deployment Platform handles a vast number of AI/ML projects and allows for streamlining the process of creating, testing, and deploying to production Artificial Intelligence and Machine Learning models for Data Science teams. Developers are guided through the company's deployment processes and supported with reusable blueprints that can be leveraged at the initial steps of the development.

Along with the environment empowering the development of exceptional AI-powered software, the customer reduced code by 80% while retaining high quality and testability. The created cloud-native toolset provides flexibility and agility, supporting innovation.

All those solutions allowed Grape Up to help the customer enable its AI software development teams to work more efficiently and reduce time-to-market for new products and services.


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