Beam provides a serverless cloud infrastructure that enables developers to deploy AI inference APIs, train models, and manage task queues with automatic GPU scaling. This platform addresses the challenges of slow deployment times and infrastructure management, allowing users to focus on building applications while only paying for the resources they consume.
Funding
Funding not disclosed
Founders
Product
Problem
Deploying AI inference APIs, training models, and managing task queues often involves complex infrastructure management and slow deployment times, diverting resources from core application development. Traditional cloud solutions can be expensive, requiring users to pay for idle resources and manage scaling manually.
Solution
Beam provides a serverless cloud infrastructure designed to streamline AI development and deployment. The platform enables developers to deploy inference endpoints, train AI models, and manage task queues with automatic GPU scaling. Beam offers fast cold starts and allows users to focus on building applications, paying only for the resources they consume. By abstracting away infrastructure complexities, Beam accelerates development cycles and reduces operational overhead for AI-powered applications.
Target Audience
Beam targets AI developers and companies of all sizes who need a fast, scalable, and cost-effective platform for deploying and managing AI workloads.
Features
- Serverless deployment of inference APIs with a single command
- Automatic GPU autoscaling based on queue depth
- Support for training LLMs and GenAI models
- Globally distributed cloud volumes for data management
- Hot reloading for rapid iteration
- Easy local debugging with production-like configurations
- Integration with GitHub Actions for CI/CD pipelines
- Support for multiple workers per container
- Realtime Websocket Client