Overview
Cast AI is a venture-backed cloud cost optimisation platform headquartered in Miami with a primary engineering centre in Vilnius, Lithuania. The company was founded in 2019 and operates as a private organisation, with annual revenue reported in the US$15–42 million range across analyst databases as of 2025. Cast AI closed a US$108 million growth round in April 2025, bringing total funding past US$190 million and placing the company among the most heavily capitalised Kubernetes-centric FinOps vendors.
The platform focuses on autonomous Kubernetes optimisation across AWS, Microsoft Azure, and Google Cloud. Cast AI's core differentiation is automated bin packing, spot instance orchestration, and right-sizing executed against live workloads rather than reported as recommendations. Buyers typically deploy Cast AI in production within two to four weeks; the platform inserts itself as a custom scheduler in the customer's Kubernetes clusters and continuously rebalances pods onto cheaper compute. Customers using Cast AI report average compute cost reductions of 40–65% on optimised clusters, with the company managing several billion dollars in annual cloud spend across its installed base.
Cast AI fits engineering-led organisations that run material Kubernetes estates on hyperscalers and are willing to grant the platform automation rights. The product is a poor fit for organisations whose workloads sit primarily on traditional VMs, serverless functions, or managed PaaS offerings outside Kubernetes. Cast AI does not replace a full FinOps practice — it complements one by automating the execution layer rather than the allocation or chargeback layer.
Services Offered
- Autonomous Kubernetes cluster optimisation and bin packing
- Spot instance automation with fallback to on-demand
- Workload right-sizing based on observed resource usage
- Multi-cloud cost visibility for AWS, Azure, and Google Cloud
- Database optimisation for RDS, Aurora, and equivalent managed services
- Cluster security posture management and rebac integration
- Commitment and reservation portfolio management
- Custom scheduler installation and Helm-based deployment support
- Reporting, chargeback, and showback dashboards
- GPU workload optimisation for AI training and inference clusters
Typical Engagement
| Engagement Type | Model | Typical Range |
|---|---|---|
| Free assessment scan | No-cost cluster analysis | $0 (2–5 days) |
| Production deployment | Annual platform subscription | $50K–$1M+ ACV depending on cluster spend |
| Performance-linked pricing | Percentage of verified savings | 15–25% of savings delivered |
| Enterprise managed plan | Monthly retainer with SLA | $10K–$80K per month |
| Professional services | Hourly bill rate (limited) | $200–$300/hour |
Pricing verified May 2026 from public procurement data and reference checks; ranges vary by region and engagement structure.
Strengths
- Documented compute cost reductions of 40–65% in production Kubernetes clusters across reference customers
- Automation-first model — savings execute without requiring engineering teams to action recommendations manually
- Free read-only scan offered before commercial commitment, lowering procurement risk
- Strong spot instance handling with interruption fallback logic across AWS, Azure, and Google Cloud
- Performance-linked commercial structures available for buyers who prefer outcome-based contracts
- Active development pace — quarterly releases against a published roadmap
Limitations
- Coverage is concentrated on Kubernetes — non-containerised workloads, serverless, and managed PaaS are out of scope
- Automation requires granting Cast AI cluster-admin permissions, which some regulated industries restrict
- Smaller services and support footprint than incumbent FinOps tools — expect lean account teams
- Less mature reporting and chargeback features than dedicated FinOps platforms such as Apptio Cloudability or Flexera One
- Private-company commercial transparency is limited compared with publicly listed competitors