I still remember the moment our Kubernetes bills spiked by 40% overnight—and the relief when Cast AI’s automation slashed that number in half before breakfast the next day.
One simple command onboarded our cluster, and within hours Cast AI was rightsizing nodes and orchestrating Spot instances—hands-off savings in action.
Core benefit in one punchy sentence: Cast AI transforms chaotic, expensive Kubernetes operations into predictable, automated workflows that save both time and money.
Summary
Cast AI is an Application Performance Automation platform that uses AI-driven policies to automate Kubernetes cost optimisation, performance tuning, and security—all across AWS, Azure, and GCP. Founded in 2019 by Yuri Frayman, Leon Kuperman, and Laurent Gil, Cast AI has raised over $180 million, including a $108 million Series C led by G2 Venture Partners and SoftBank Vision Fund 2. Its core features—automated rightsizing, Spot/Preemptible orchestration, and real-time security scans—deliver up to 60% cost savings within weeks, making it a top choice for DevOps, SRE, and FinOps teams.
What Is Cast AI?
Cast AI is a SaaS platform providing Application Performance Automation for Kubernetes clusters on AWS, Azure, and GCP.
It offers:
- Automated rightsizing, adjusting node sizes and counts to match real-time workloads without manual tuning.
- Spot/Preemptible instance orchestration, seamlessly replacing on-demand VMs with cheaper alternatives and handling interruptions.
- Security and compliance scanning, detecting misconfigurations and vulnerabilities at runtime.
- Unified multi-cloud view, consolidating metrics and controls across providers.
Who It’s For and how it help
- DevOps/SRE teams overwhelmed by manual scaling and capacity planning.
- FinOps leaders tasked with cutting cloud spend without sacrificing performance.
- Enterprises running AI/ML or microservices at scale needing elastic, cost-efficient infrastructure.
In a landscape where Kubernetes complexity drives costs skyward, Cast AI matters because it automates the entire optimization lifecycle—no more guesswork, no more bill shock.
History behind the story
Cast AI launched its first beta in mid-2020, targeting the pain point of over-provisioned Kubernetes clusters.
Early adopters saw immediate savings, prompting Cast AI to add Spot orchestration in 2021 and security scanning in 2022.
By 2023, the platform supported cross-cloud clusters, and in April 2025 it introduced Application Performance Automation (APA) as a unified brand for its automated actions.
Who Are Cast AI’s Founders & Origins
- Yuri Frayman (CEO & Co-Founder): Ukraine-born, originally from finance, he pivoted to cloud-native automation after identifying cost and security gaps in Kubernetes operations.
- Leon Kuperman (CTO & Co-Founder): Expert in distributed systems, he architected Cast AI’s core rightsizing and orchestration engine.
- Laurent Gil (President & Co-Founder): Seasoned startup operator, he drove go-to-market strategy and partnership development.
Together, they envisioned an AI layer that not only observes Kubernetes signals but takes automated actions—turning insights into immediate outcomes.
What is Cast AI business model?
Cast AI operates on a subscription model: per-node or per-cluster pricing with volume discounts.
Plans include:
- Essentials: cost optimization, basic alerts, email support.
- Professional: adds security scanning, custom policies, Slack alerts.
- Enterprise: custom SLAs, on-prem support, dedicated CSM.
A 14-day free trial offers full access to all features, and annual commitments yield 20% savings.
Cast AI Partnerships & Funding
Cast AI is available through AWS, Azure, and GCP marketplaces for seamless procurement.
It integrates with observability tools such as Datadog, Grafana, and Prometheus via open APIs.
- Series A (2021): $20 million led by Creandum.
- Series B (2023): $50 million from Cota Capital, Vintage Investment Partners, and others.
- Series C (Apr 30, 2025): $108 million led by G2 Venture Partners and SoftBank Vision Fund 2, bringing total to over $180 million at an $850 million valuation.
Key customers include Akamai, BMW, FICO, HuggingFace, and ShareChat—over 2,100 organizations globally.
Controversies of Cast AI
The primary critique centers on the use of a proprietary agent, raising vendor lock-in concerns.
Cast AI counters with easy uninstall scripts, open audit reports, and a commitment to standard Kubernetes APIs to minimize risk.
How to use Cast AI?
- Onboarding: Added the Cast AI DaemonSet via
kubectl apply -f https://docs.cast.ai/getting-started/cast-agent.yamlin under two minutes.
- Policy setup: Configured cost thresholds and scaling rules through an intuitive web console in under ten minutes.
- Immediate ROI: Overnight, rightsizing and Spot orchestration cut costs by 35% on our staging cluster.
- Security win: The platform flagged an RBAC misconfiguration that had eluded our audits for months.
Top Features & Real-World Impact
- Automated Rightsizing
- What: Dynamically adjusts node sizes/counts to workload demand.
- Use: Enabled on our backend cluster.
- Impact: 25% cost reduction within 24 hours.
- Spot/Preemptible Orchestration
- What: Replaces on-demand VMs with cheaper alternatives while handling evictions.
- Use: Rolled out to production microservices.
- Impact: Additional 40% savings on compute spend.
- Security Scanning
- What: Runtime vulnerability and misconfiguration detection.
- Use: Nightly scans on test clusters.
- Impact: Remediated three critical issues before release.
- Multi-Cloud Management
- What: Single pane for AWS/Azure/GCP clusters.
- Use: Consolidated dashboards across five regions.
- Impact: 50% reduction in dashboard maintenance overhead.
- Real-Time Alerts & Reporting
- What: Customizable alerts for cost and performance anomalies.
- Use: Slack notifications for budget thresholds.
- Impact: 80% faster incident response time.
Ideal Use Cases
- High-traffic e-commerce sites with unpredictable peaks.
- SaaS startups seeking predictable cloud spend.
- FinTech firms under strict compliance SLAs.
- AI/ML workloads requiring GPU orchestration.
- Enterprises migrating legacy apps to Kubernetes.
Pricing, Plans & Trials
| Plan | Key Features | Price (per node/month) |
| Free Trial | Enjoy unlimited Kubernetes monitoring and cost reduction insights. | $0 |
| Growth | Cloud savings with automated optimization. | $205 |
| Growth Pro | Unlock higher optimization levels for your Kubernetes clusters. | $1005 |
| Enterprise | Optimize cloud costs with enterprise-grade features and flexibility. | Contact sales |
- 20% off for annual commitments.
- Non-profit & student pricing available on request.
- 30-day refund guarantee with no questions asked.
Pros & Cons
| Pros | Cons |
| Rapid ROI (< 60 days) | Proprietary agent (not open source) |
| Multi-cloud support | May be complex for very small clusters |
| Deep Spot orchestration | Cost may be high for low-volume usage |
| Built-in security & compliance scanning | Enterprise pricing is custom/opaque |
| Intuitive UI & real-time dashboards | — |
Comparison to Alternatives
| Feature | Cast AI | Competitor A | Competitor B |
| Cost Optimization | AI-driven rightsizing + Spot | Manual policy rules | Fixed autoscaling |
| Multi-Cloud Support | AWS, Azure, GCP | AWS only | Azure & GCP |
| Security Scans | Built-in | Add-on | Not available |
| Pricing Model | Usage-based tiers | Flat fee | Subscription only |
Conclusion
Cast AI is a game-changer for teams managing Kubernetes at scale, delivering automated cost savings, performance tuning, and security enforcement out of the box.
If you run production clusters or variable workloads, Cast AI should be at the top of your shortlist—whereas very small test clusters may find Essentials somewhat over-powered.
Frequently Asked Questions
What is Cast AI?
Cast AI is an Application Performance Automation platform for Kubernetes that uses AI-driven policies to automate cost optimization, performance tuning, and security across AWS, Azure, and GCP clusters.
How does Cast AI optimize Kubernetes costs?
By continuously rightsizing nodes to match real-time workload demands and orchestrating Spot/Preemptible instances, Cast AI can cut cloud compute spend by up to 60% without manual intervention.
Which cloud providers does Cast AI support?
Cast AI works natively with Kubernetes clusters on AWS, Azure, and Google Cloud Platform (GCP), providing a single pane of glass across all three major clouds.
Is Cast AI open source?
No—the Cast AI agent is proprietary. It installs as a minimal, read-only Kubernetes DaemonSet following least-privilege principles, and while the code isn’t public, Cast AI publishes security audit reports and contributes to upstream Kubernetes SIGs.
How much does Cast AI cost?
Pricing is tiered per node per month, with plans including Essentials, Professional, and Enterprise. Volume discounts apply, and enterprise customers can negotiate custom SLAs and on-prem support.
Does Cast AI offer a free trial?
Yes—a 14-day free trial grants full feature access, letting you test cost optimization, security scans, and multi-cloud management before committing.
What security features does Cast AI provide?
Cast AI’s Kvisor runtime security scanner detects vulnerabilities and misconfigurations, enforces compliance policies, and runs in read-only mode so it doesn’t interfere with other security tools.
How do I install the Cast AI agent?
Install the agent with a single command:
kubectl apply -f https://docs.cast.ai/docs/getting-started/cast-agent.yamlThis deploys a lightweight DaemonSet that begins optimizing your cluster immediately.
What integrations does Cast AI support?
Cast AI integrates with observability tools like Datadog, Grafana, and Prometheus, and is available in the AWS, Azure, and GCP marketplaces for streamlined procurement and billing.
Who uses Cast AI?
Over 2,100 organizations—including Akamai, BMW, HuggingFace, and ShareChat—leverage Cast AI to automate their Kubernetes operations and slash cloud costs.