The autonomous engine for modern app & AI performance
Cast AI’s autonomous agents take real action in production:
rightsizing CPU, memory, and GPU, scaling nodes on demand, and keeping cloud-native and AI environments healthy.
Anywhere you run Kubernetes.
Trusted by 2100+ companies globally
Problem
Your apps need constant tuning.
Your team can’t keep up.
Most tools surface the problem and stop there. Your team still has to fix it manually, repeatedly, at 3am.
Recognition
Recognized for performance
High customer ratings and global certifications show Cast AI delivers where it matters most.
application performance automation platforM
One platform. Full-stack optimization. Zero manual fixes.
Cast AI continuously optimizes in real time based on actual workload behavior. It doesn’t just show you what to fix, it fixes it for you. No more tickets, no more alerts.
Self-healing operations
AI Agents that fix real issues. Remediate drift, update container images, auto-heal failures, and enforce policies. No tickets. No waiting.
Enterprise-grade security
Performance observability & intelligence
Real-time visibility into resource utilization and application performance. Know exactly how your apps behave, continuously.
Enterprise-grade security
Workload rightsizing
Automatically adjust CPU and memory requests to match actual usage. Eliminate over-provisioning without risking performance. Every workload is continuously tuned.
Enterprise-grade security
Infrastructure automation
Scale nodes up and down based on real demand. Optimize GPU allocation. Automate spot instance management. One control plane across any cloud or on-prem.
Enterprise-grade security
Cast Engine
The performance engine for your cloud-native applications
Infrastructure that adapts to your code, not the other way around.
Most automation relies on static rules. The Cast AI Engine is different. We’ve built an advanced predictive model for Kubernetes, trained on a massive dataset from thousands of clusters and millions of real-world workloads. By analyzing the DNA of application demand, our engine moves beyond “if-then” logic:
App-aware reliability
Predicts spot interruptions up to 30 minutes before they happen, migrating workloads gracefully before your users feel a slowdown.
Precision rightsizing for stability
Adjusts CPU and memory at the millicore level to prevent resource starvation and “noisy neighbor” issues.
Intelligent workload placement
Instantly matches every pod to its optimal instance type, ensuring high-demand AI and data workloads run on the best possible hardware.
How it works
From connect to optimized in minutes
Connect
Deploy to your Kubernetes clusters in minutes. Start in read-only mode. No infrastructure changes required.
Analyze
The platform observes real workload behavior, not static configurations, and identifies optimization opportunities.
Optimize
Cast AI automatically scales, rightsizes, and rebalances based on real-time signals, not scheduled jobs.
Fix
Use agentic runbooks to fix operational and security issues for you. You approve every change before it ships.
Integrations
Works with the tools you already use
Case study
Akamai achieves 40-70% cloud savings, boosts engineer productivity
“I had an aha moment – an iPhone moment – with Cast. Literally two minutes into the integration, we saw the cost analytics, and I had an insight into something I had never had before and had tried to get for a very long time.”
Dekel Shavit
Sr. Director of Engineering
Case study
Yotpo automates Spot Instances, cuts 40% in cloud costs and saves time
“And with Cast AI, we didn’t do anything. Like, we didn’t do the move before, we didn’t do the move after. So there was a lot of human resources and time saved here. That was a very good experience. And again, from a cost perspective, it was highly optimized.”
Achi Solomon
Director of DevOps
Case study
Bede Gaming automatically optimizes K8s workloads with no risk to performance
“In my mind, it’s one less thing to worry about, and therefore teams can be focused on other things of potentially higher value. So having [Cast AI] just run in the background with a good level of confidence that we’re running as efficiently as we can, balancing the service that we’re providing – that’s great.”
Dan Whiteley
Chief Technology Officer
TESTIMONIALS
See what people say about Cast AI
Abhiroop Soni
Staff Engineer – DevOps at ShareChat
“I don’t have to do anything manually and we’re close to 98% commitment utilization. I used to do capacity planning twice a week for CUD management – now I do that once every two months.”
Nicolas Hug
Lead SRE at Voggt
“Cast AI gets the perfect machine for the workload every time.”
Johannes G.
Expert Lead Cloud and DevOps
“We already during the POC, were able to reduce the Instance Costs by arround 30%, so the product payed for itself. Because of that it was very easy to convince the management to buy the product.”
Achi Solomon
Director of DevOps at Yotpo
“The ROI was great right from the start. Reducing 40% of our compute costs just by migrating our workloads to Cast AI—that’s huge. And we haven’t even utilized all the CAST features up until now, just the automated instance selection, bin packing, and Spot instance automation.”
Ron G.
VP R&D
“Cast does a great job at optimizing the workload, thus reducing the cloud costs. we were pretty optimized already and it still saved us around 30-40% of the total costs(!).”
Dekel Shavit
Senior Director of Engineering at Akamai
“For our use case, CAST was not two times better or five times better. It was immeasurably better.”
Rafael Tovar
Google Cloud Operation Leader
at Open Assessment Technologies
“Thanks to Cast AI, it was the first time that I took a vacation for a month, and nobody asked me to add more nodes to their applications because they’re running a new campaign. I was super happy because of that.”
Jenson C S
Senior Engineering Manager at ShareChat
“In terms of the Infrastructure or DevOps team, the Kubernetes management effort such as manual rightsizing, creation of node pools, and upgrade efforts are drastically reduced, so the DevOps team can focus on building products to improve developer productivity.”
James O’Hare
Principal Platform Engineer at NielsenIQ
“Cast AI paid for itself close to within the first two months thanks to all the savings it generated around compute costs.”
Mark Weiler
Ex-Senior VP of Engineering at Branch
“Partnering with CAST AI has been a big success for Branch, saving us several millions of dollars per year in AWS Cloud compute costs for our Kubernetes clusters while maintaining our reliability SLAs.”
Achi Solomon
Director of DevOps at Yotpo
“After integrating Cast AI, we didn’t have to do anything during Black Friday, which is amazing. We gained not just compute cost reduction but also a reduction in engineer workload.”
Cameron L.
System Analyst
“Support has aslo been a high-point when working with CAST. In the rare occasion that we have encountered any issues they have been extraordinarily responsive and dedicate resources to assist with our problem until it is resolved, no matter the time of day or night.”
2100+ companies choose Cast AI.
4.8/5 50+ reviews