Covalent
Share
Covalent
Orchestration platform to run and scale AI workflows. Automatically manages GPU and CPU resources for complex tasks without managing infrastructure.
General Information about Covalent
Covalent is an advanced compute infrastructure solution specifically designed for developing, executing, and scaling artificial intelligence applications and complex computational workflows. This compute orchestration platform allows developers, researchers, and data scientists to manage intensive tasks without the need to directly manage underlying hardware or configure complicated server environments. By acting as an abstraction layer, Covalent facilitates the transition from prototypes developed on a local computer to large-scale executions in the cloud or hybrid infrastructures.
The primary function of this tool is to automate the provisioning and management of critical hardware resources, including high-performance graphics processing units (GPUs) such as the Nvidia H100, A100, L40, or A10G, in addition to standard CPUs. Through seamless integration with Python and other common programming tools, users define their workflows, and the platform handles code packaging, container management, and efficient workload distribution. This approach eliminates operational barriers in AI model training projects, inference, big data processing, and scientific simulations.
The operation of Covalent is based on a distributed and scalable execution model. The operational workflow can be summarized in the following points:
- Task Definition: The user programs tasks or workflows via code, specifying the computing requirements necessary for each step.
- Infrastructure Management: The platform automatically provisions resources, whether in the Covalent cloud, on-premises infrastructures, or hybrid environments.
- Automatic Orchestration: It manages the lifecycle of clusters and containers, distributing jobs to maximize the utilization of available resources.
- Monitoring and Results: It enables real-time tracking of distributed workloads and returns results centrally once computations are complete.
This technology is essential for technical professionals developing Large Language Models (LLMs), computer vision systems, or high-performance computing (HPC) applications. By centralizing orchestration, companies can optimize the use of shared resources and more effectively implement internal hardware consumption policies.
For industry professionals, Covalent provides practical benefits by drastically reducing the time spent on DevOps tasks and system configuration. Its ability to offer on-demand GPU resources ensures that AI projects are not limited by local hardware capacity, allowing for seamless scaling according to the needs of each research project or product.
Features and Use Cases of Covalent
How Covalent Works
Frequently Asked Questions about Covalent
What is Covalent, and what are its benefits for developers?
It is an infrastructure solution that allows you to run heavy compute tasks and AI workflows without worrying about server management.
How do I integrate my Python programs with Covalent?
You just need to define your functions and tasks in code, and the platform handles packaging everything needed to run them in the cloud or on local resources.
What kind of processing hardware can I use on the platform?
You have access to a wide range of processing units, including CPUs and high-performance NVIDIA GPUs such as the H100 and A100 models.
How does Covalent’s billing work?
The service follows a pay-as-you-go model where costs are calculated based on the exact time resources are used, with no fixed subscription fees required.
Is there an option to try Covalent without an upfront payment?
The platform provides a twenty-dollar credit to new users, allowing them to run their first tasks and performance tests for free.
What if my company needs a custom solution?
For large organizations, we offer specific plans that include advanced support and the ability to manage hybrid or on-premises infrastructure based on their needs.
What are the primary use cases for Covalent?
It is ideal for training machine learning models, complex scientific simulations, computer vision, and large-scale data processing.
Covalent Pricing
Free Trial: 20 USD Free Credit
- Allows you to test the platform and run your first tasks at no upfront cost.
Cloud (Pay-As-You-Go): No fixed monthly fees
- On-demand access to compute resources (CPU and GPU) with billing based exclusively on actual usage time.
- Billing calculated by the minute or by the hour of execution.
- Estimated GPU rates: Nvidia H100 (2.15 USD/hr), Nvidia A100 (1.49 USD/hr), Nvidia L40 (1.60 USD/hr), Nvidia A10G (1.21 USD/hr), and RTX A4000 (~0.17 USD/hr).
- Estimated rate for basic CPU: starting at ~0.15 USD/hr.
- Automated infrastructure orchestration, container management, and workflow deployment via Python.
Enterprise: Custom Pricing (Contact Sales)
- Tailored solutions for large organizations and mission-critical workloads.
- Includes additional specialized technical support.
- Advanced options for managing and monitoring shared resources according to internal policies.
- Support for on-premises, hybrid, or private cloud deployment.
Covalent Screenshots
