Cerebrium is a data and AI platform that enables businesses to deploy applications without the need for a dedicated data team, utilizing efficient build processes and low-latency inference. The platform optimizes resource allocation and costs, ensuring applications are live in seconds while maintaining 99.999% uptime and compliance with security standards.
Funding
$500K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Deploying and scaling AI applications often requires specialized data teams and complex infrastructure management, leading to increased operational overhead and slower deployment times. Optimizing resource allocation and ensuring high availability while adhering to security and compliance standards presents further challenges.
Solution
Cerebrium provides a platform designed to streamline the deployment and scaling of AI applications, eliminating the need for dedicated data teams. The platform focuses on efficient build processes and low-latency inference, enabling applications to go live rapidly. By optimizing resource allocation, Cerebrium reduces costs while maintaining 99.999% uptime. The platform also incorporates features for real-time logging, cost management, and comprehensive observability, providing developers with the tools they need to monitor and manage their applications effectively. Cerebrium supports various hardware configurations, including CPUs and GPUs, allowing users to select the optimal resources for their specific needs.
Target Audience
Cerebrium targets businesses and developers looking to deploy and scale AI applications quickly and efficiently, particularly those in need of optimized resource allocation, high availability, and robust security features.
Features
- Rapid application deployment with build times averaging under 11 seconds
- Low-latency inference, adding less than 50ms of overhead to request processing
- Real-time logging for quick identification and resolution of deployment issues
- Cost management tools for tracking spend and resource allocation
- Comprehensive observability features for monitoring application health
- Support for various hardware configurations, including CPUs, Tranium, Inferentia, L4, L40s, A10, T4, A100 (80GB), A100 (40GB), and H100 GPUs
- Automatic autoscaling to handle varying traffic loads
- Support for TensorRT for optimized inference performance
- SOC 2 and HIPAA compliance for secure data handling