Cerebrium AI (Web Development)
Screenshot of Cerebrium AI

Cerebrium AI

Discover what Cerebrium AI is — a scalable machine learning platform with pay-per-millisecond pricing, low latency, and SOC 2 compliance.

Screenshot

What is Cerebrium AI?

Cerebrium AI is a platform that provides developers with the computing power needed for machine learning projects. It is built to scale from hobbyist projects to larger ML applications managed by teams.

Pricing is pay-as-you-go: you pay only for the exact compute resources you use, down to the millisecond, with no hidden fees. The platform is designed to speed up inference pipelines, streamline workflows, and keep latency low for real-time responsiveness.

Key features include:

  • Reliability: Targets 99.999% uptime.
  • Security: SOC 2 compliant, with secure data handling.
  • Real-time logging: Spot deployment issues quickly.
  • Cost tracking: Tools to monitor spending.
  • Observability: Monitor your application’s health.
  • GPU options: A range of GPUs from different cloud providers.
  • Autoscaling: Handled automatically to keep applications running smoothly.

Who created Cerebrium AI?

Cerebrium was built by a team focused on making applications perform better and run more cost-efficiently. Their goals are real-time performance, low latency, and high uptime, with reliability and SOC 2 compliance as priorities.

How to use Cerebrium AI?

  1. Get started: Visit the documentation at https://docs.cerebrium.ai/.
  2. Build voice agents: The platform is designed to optimize inference performance, offering low latency and 99.999% uptime.
  3. Track and manage: Use real-time logging to spot deployment issues and manage costs efficiently.
  4. Monitor your app: Use observability tools to understand application performance.
  5. Choose your GPU: Select from a variety of GPUs across different cloud providers, with extra capacity available.
  6. Rely on autoscaling: Applications scale automatically with demand.

Pricing and plans

Cerebrium offers plans for different needs:

  • Hobby: For developers just starting out.
  • Standard: For ML apps already in production.
  • Enterprise: For teams scaling their ML applications.

On-demand pricing applies to both GPU and CPU compute, so you pay only for what you use. If you’re considering AI at your company, you can try the platform with up to $1,000 in free credits, which includes access to expert engineers for guidance.

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