Devopsbay contributed to the development of a solution that simplifies the deployment and maintenance of AI/ML models by offering advanced tools to control the entire lifecycle of the algorithms. We helped implement key features such ascentral model management, flexible deployment across environments and automated performance monitoring.
The platform provides a central place to control all aspects of models, from deployment to monitoring and scaling. Algorithmia is distinguished by its flexibility, enabling implementation in a variety of environments, and automatic performance monitoring to help maintain high quality predictions. Additionally, the platform supports integrations with popular ML/AI tools, making it easy to integrate into existing processes and systems within an organisation.
Making MLops easier to implement and scaling in different configurations.
ScalaUsed to implement extension code and integrate with external systems, Scala allows for robust backend solutions.
KafkaServes as an event-handling system, enabling the automation of running algorithms in response to events through integration with Kafka messaging.
Bitbucket SCM IntegrationAlgorithmia extends its source code management capabilities by integrating with Bitbucket, which supports better collaboration and version control.
KubernetesUsed to deploy and manage containerised applications, ensuring scalability and reliability of platform services.
Algorithmia has become the complete platform for managing the lifecycle of AI/ML models in a production environment. The platform now offers a wider range of integrations, improved process automation, central model management, and advanced monitoring tools. This allows companies to deploy, manage and monitor their AI/ML solutions more efficiently, while increasing the scalability and flexibility of these solutions.
Expanding integration optionsAutomatic monitoringImproved source code managementDeployment flexibilityCentral model manageAlgorithmia has enhanced its platform by adding new integration options, such as support for Kafka as an event system and integration with Bitbucket for source code management. This has extended the platform's functionality and increased its flexibility.
Algorithmia provides real-time monitoring of model performance, automatically tracking metrics like accuracy and response time. This ensures timely detection of issues, reducing manual oversight and maintaining model reliability.
Integration with Bitbucket SCM has expanded source code management options, enabling better collaboration and version control for users of the platform.
The platform now allows models to be deployed in a variety of environments - locally, in the cloud, or on hybrid systems, increasing its flexibility and adaptation to the needs of different customers.
Algorithmia has created a central place to deploy, monitor and manage all production models, regardless of how they were created or where they are deployed.
Algorithmia has enhanced its platform by adding new integration options, such as support for Kafka as an event system and integration with Bitbucket for source code management. This has extended the platform's functionality and increased its flexibility.
Devopsbay helped create an effective system to automate and manage the lifecycle of machine learning models, significantly speeding up the process of deploying them into a production environment.
By implementing solutions based on containerization and orchestration, the client has gained the ability to flexibly scale the infrastructure according to current needs.
The introduction of serverless architecture and intelligent resource management has significantly reduced the operational costs associated with maintaining AI/ML infrastructure.
The implementation of advanced tools to monitor and analyze the performance of ML models has enabled faster detection and resolution of potential problems.
Devopsbay delivered functionally stable and highly satisfactory software that was a leader in the industry. The technically skilled team effectively utilized various technologies to support efficient collaboration.
The Devopsbay Defense platform is an innovative approach to managing AI technologies in military environments. It is a complete DevSecOps solution with a security focus that meets strict DoD criteria.
Devopsbay helped a multinational manufacturing company on a project to speed up the data preparation process by 70% by implementing DataRobot Data Prep. The project focused on automating the cleaning and transformation of data from multiple sources, significantly reducing the time required to prepare data for analysis.
The {descrb} project aimed to optimise e-commerce costs by automating the creation of product descriptions. We used the synergy of NLP models and our own hosted LLama for better data control. We also implemented a Confidence Index to assess the quality of the content generated. The results? A reduction in description creation time from 30 minutes to less than a minute, an increase in conversions by 25% and traffic by 10%.
