C
CAST AI
AI · Miami, United States · Founded 2019
Automated Kubernetes cost and resource optimization. MoreLess
Cast AI keeps your applications fast, stable, and self-healing - automatically. Instead of your engineering team manually tuning Kubernetes clusters, Cast AI's engine learns from thousands of real clusters and millions of workloads to predict what your apps need before problems happen, Cast AI constantly adjusting resources so your services hit their performance targets without anyone touching a config file. It fine-tunes CPU and memory down to the millicore level to stop resource starvation and noisy-neighbor issues Cast AI - the kind of things that cause latency spikes and missed SLOs at 2am. When spot instances are about to be interrupted, the platform sees it coming up to 30 minutes ahead and moves workloads gracefully, so your users never notice. Cast AI Predictive autoscaling looks up to three days into the future to forecast demand, and startup-aware resource management prevents containers from failing health checks during restarts Cast AI - meaning your apps scale smoothly instead of crashing under pressure. Agentic runbooks automatically detect and fix operational and security issues, with approval gates so your team stays in control Cast AI without being stuck in a reactive firefighting loop. At the database layer, the Database Optimizer works as an autonomous caching layer that speeds up queries Cast AI without touching your application code. For teams running AI workloads, Kimchi.dev acts as a centralized gateway that routes requests across both SaaS providers like OpenAI and Anthropic and self-hosted models running in your own infrastructure, Cast AI intelligently selecting the right model for each request based on complexity Cast AI while giving you a single endpoint, a built-in playground for benchmarking, and full data sovereignty when you need it. And with OMNI Compute, teams can provision and run GPU capacity across any cloud provider or region without changing a line of code, Cast AI so meeting latency and throughput requirements doesn't depend on getting lucky with capacity in a single region. The bottom line: Cast AI turns infrastructure from something your team constantly worries about into something that just works - and the cost savings are a side effect of running everything at exactly the right size, in the right place, at the right time.
Keywords: Kubernetes cost optimization, Kubernetes automation platform, cloud cost optimization, Kubernetes autoscaling, workload rightsizing, spot instance automation, reduce cloud costs, EKS cost optimization, GKE cost optimization, AKS cost optimization, GPU optimization Kubernetes, LLM infrastructure optimization, cloud infrastructure automation, Kubernetes node provisioning, container rightsizing, FinOps automation Kubernetes, Kubernetes resource optimization, Cast AI, Karpenter, Application Performance Automation, Gartner Hype Cycle AIOps, Forrester cloud cost management landscape, G2 cloud cost management leader, IDC Innovator FinOps, Kubernetes cost benchmark report, OMNI Compute, Kimchi LLM gateway
Talent graph
CAST AI's talent
Source: Dealroom Talent Intelligence.
Global footprint
Where CAST AI has talent and traffic
team presence
across markets
Patent intelligence
$2M patent portfolio · 18 active families
Where CAST AI concentrates vs peers
Each axis is a top-10 topic across CAST AI and its closest peers. #1 = 100, #10 = 10, absent = 0.
Source: Dealroom Patent Intelligence · Patsnap. Request a demo for the full per-sub-category breakdown, individual records, and quality-score history.
Market sentiment
What the market is saying about CAST AI
An AI-synthesized read of the highest-engagement posts about CAST AI on X over the past 7 days. We rank by likes & retweets, ignore corporate channels, and surface the themes that broke out from real people.
Reading the room on X — pulling top posts and synthesizing themes…
Source: X recent search ranked by engagement (likes + retweets) · Synthesis by Claude · Cached for 1 hour
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