CAST AI
Company Information
Headquarters
Miami, Florida, USA
Year Founded
2019
Industries
Cloud Computing, Information Technology, Software Development, Financial Services, E-commerce, Telecommunications
What Is CAST AI?
CAST AI is an AI-powered cloud infrastructure automation company that develops software for optimizing Kubernetes, cloud-native applications, databases, and AI compute. Its platform uses automation and intelligent resource management to continuously adjust infrastructure according to workload requirements. CAST AI works across major cloud environments, including AWS, Google Cloud, and Microsoft Azure, and has expanded its technology into GPU infrastructure optimization and autonomous DevOps operations.
What Does CAST AI Do?
CAST AI automates infrastructure tasks that engineering teams traditionally manage manually, including resource provisioning, workload rightsizing, autoscaling, node selection, Spot Instance management, and cloud cost monitoring. Its Kubernetes platform analyzes actual resource requirements and can automatically adjust compute capacity as workloads change, rather than relying only on static infrastructure configurations.
The company also applies its automation technology to AI infrastructure, where organizations need to manage expensive and sometimes scarce GPU resources. CAST AI’s tools can help engineering teams allocate CPU, memory, and GPU resources more efficiently while maintaining application performance and availability across cloud environments.
CAST AI Technology
CAST AI combines AI-driven infrastructure automation, Kubernetes orchestration, workload telemetry, autoscaling, resource scheduling, and cloud cost intelligence. The platform continuously analyzes workload behavior and infrastructure requirements instead of treating cloud optimization as a one-time configuration exercise.
For Kubernetes environments, CAST AI can automatically provision compute resources, consolidate workloads through bin packing, manage Spot Instances, adjust pod resources, rebalance clusters, and scale workloads vertically and horizontally. Its OpsPilot AI agent interprets telemetry and operational signals to autonomously create and optimize workload policies.
For AI workloads, OMNI Compute extends Kubernetes compute across clouds and regions, allowing workloads to access GPU, TPU, and CPU capacity through a unified control plane. The technology also supports GPU sharing and intelligent node selection. CAST AI has extended its automation approach beyond Kubernetes infrastructure with an ML-driven database caching system and a multi-model AI coding agent.
Why CAST AI Matters
CAST AI is relevant to the emerging AI infrastructure landscape because increasing AI adoption is creating new challenges around GPU utilization, cloud costs, and infrastructure complexity. AI training and inference workloads can require large amounts of compute, while demand and resource requirements can change quickly.
CAST AI applies autonomous infrastructure management to this problem, allowing compute resources to respond dynamically to workload requirements rather than depending entirely on manual configuration. Its expansion from Kubernetes optimization into multi-cloud GPU management, autonomous DevOps, databases, and AI development reflects a broader shift toward software-defined, AI-managed infrastructure that can continuously optimize itself as application conditions change.
CAST AI Products & Platforms
Kubernetes Automation & Optimization
CAST AI’s Kubernetes platform provides automated infrastructure and workload optimization. It includes cluster autoscaling, workload rightsizing, bin packing, Spot Instance automation, commitment utilization, pod optimization, cost monitoring, and resource rebalancing. The system can continuously match Kubernetes resources to actual workload requirements across supported cloud environments.
OpsPilot
OpsPilot is CAST AI’s AI agent for DevOps and site reliability engineering. It analyzes telemetry and operational signals and can autonomously create and optimize workload policies. CAST AI introduced autonomous workload management through OpsPilot to reduce the manual work involved in tuning resource requests, limits, and scaling policies as applications change.
OMNI Compute for AI
OMNI Compute is a unified compute control plane designed for AI and other compute-intensive workloads. It can extend Kubernetes capacity across cloud providers and regions so workloads can access available GPU, TPU, and CPU resources through one Kubernetes environment. It incorporates capabilities such as GPU sharing, intelligent node selection, monitoring, and automated scaling.
Kimchi Coding
Kimchi Coding is CAST AI’s autonomous multi-model coding agent. Rather than depending on a single AI model, its orchestration layer routes coding tasks among different models based on task complexity and cost. CAST AI says the platform combines model routing, token optimization, enterprise controls, and self-hosted inference options for software development teams.
CAST AI Applications
CAST AI technology is primarily used in cloud-native infrastructure, Kubernetes operations, AI/ML infrastructure, and enterprise software environments. Platform engineering and DevOps teams can use it to automate resource allocation, autoscaling, workload rightsizing, infrastructure provisioning, and cloud cost management.
AI and machine-learning teams can use CAST AI to manage GPU capacity for model inference, batch processing, and other compute-intensive workloads across multiple clouds and regions. Database teams can apply Database Optimizer to PostgreSQL and MySQL workloads, while software development organizations can use Kimchi Coding for AI-assisted coding workflows.
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Frequently Asked Questions
How does CAST AI optimize Kubernetes resources?
CAST AI continuously analyzes workload requirements and can automatically modify infrastructure through rightsizing, autoscaling, bin packing, node provisioning, and Spot Instance management. This allows Kubernetes resources to adjust as application demand changes instead of relying solely on manually configured capacity.
What is CAST AI OpsPilot?
OpsPilot is an AI agent designed for DevOps and SRE operations. It interprets infrastructure telemetry and operational signals and can autonomously create and optimize workload policies, including policies affecting Kubernetes resource allocation and performance.
Can CAST AI manage GPUs across multiple clouds?
Yes. OMNI Compute for AI can extend Kubernetes compute across different cloud providers and regions, allowing workloads to consume available GPU, TPU, and CPU capacity through a unified control plane rather than being restricted to capacity in one location.
Does CAST AI work with AWS, Azure, and Google Cloud?
Yes. CAST AI supports Kubernetes environments including Amazon EKS, Google Kubernetes Engine, and Microsoft Azure Kubernetes Service. Its documentation also lists additional environments, including Oracle Cloud, Azure Government, and CAST AI Anywhere for other Kubernetes deployments.
What databases does CAST AI Database Optimizer support?
Database Optimizer currently supports PostgreSQL and MySQL, including Amazon Aurora PostgreSQL and Aurora MySQL. The system can also work with self-hosted, cloud-hosted, and managed deployments of the supported databases.
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