What ScaleOps does

ScaleOps is an autonomous cloud and AI infrastructure resource management platform founded in 2022 and headquartered in New York, with engineering and R&D operations in Tel Aviv, Israel. The company provides a closed-loop automation platform that continuously monitors and optimizes Kubernetes resources — CPU, memory, GPU, storage, and networking — in real time based on live workload behavior, eliminating the manual tuning required by traditional Kubernetes schedulers. Its product portfolio spans core infrastructure optimization (Automated Pod Rightsizing, Replica Optimization, Smart Pod Placement, Spot Optimization, Node Optimization, Karpenter Optimization, JVM-aware Java Resource Management), a dedicated GPU optimization suite for AI workloads (Automated Fractional GPUs, GPU Memory Optimization, AI Replica Optimization, Batch Inference Optimization, AI Inference Observability), observability tools (Cost Monitoring, Cluster and Workload Troubleshooting), and an AI SRE Agent for context-aware cluster investigation and controlled optimization execution. Deployment options include self-hosted (with FedRAMP/FIPS and air-gapped support) and a SaaS control plane called ScaleOps Cloud.

The platform is sold primarily through enterprise field sales with custom quote-based pricing tied to cluster count and workload complexity, supplemented by product-led growth via single Helm command installation and free trial, and distributed through AWS, Azure, and Google Cloud Marketplaces. Customers include Adobe, Salesforce, DocuSign, ServiceNow, Roku, Outbrain, Wiz, Orca Security, Coupa, DraftKings, Aurora, and Freddie Mac, spanning cybersecurity, SaaS, financial services, media, gaming, and public sector verticals. The company has raised over $210 million in cumulative venture funding across rounds in 2023, 2024, and 2026, with a $130 million Series C in March 2026 led by Insight Partners at a post-money valuation exceeding $800 million. Reported year-over-year revenue growth exceeds 350%, and the company has tripled headcount over the trailing 12 months with plans to triple again by year-end 2026.

The AI and machine learning layer is concentrated in the AI SRE Agent (general availability announced March 2026), which combines autonomous-agent behavior, anomaly detection against learned baselines, and retrieval-augmented responses over ScaleOps documentation, accessible via Slack. The underlying optimization engine uses real-time pod-level telemetry and domain-specific signals (JVM heap and garbage collection, inference metrics like time-to-first-token and prefix cache hit rate) rather than proprietary foundation models, positioning AI as a differentiated capability within a closed-loop automation system rather than as the company's core research output.

Name

ScaleOps

Legal name

ScaleOps

Website

https://scaleops.com

Company type

Private

Founded year

2022

Operating status

Operating

Headcount range

101–250 employees

Short description

ScaleOps provides autonomous Kubernetes and AI infrastructure resource optimization for enterprises, using real-time closed-loop automation to cut cloud and GPU costs across CPU, memory, storage, and AI workloads at companies like Salesforce, Adobe, and Roku.

Ownership category

akta.pro rank

Headquarters

HQ city

New York

HQ country

United States

HQ region

North America

Offices2 records

Markets served

GTM type

B2B

Offering type

Software

Cost components

Personnel, Technology or R&D, Marketing or Sales, Operations, Infrastructure

Revenue model

1. SaaS Subscription - Platform Licensing: ScaleOps operates on a subscription basis with custom pricing based on factors specific to each customer's environment including cluster count and workload complexity. The pricing model is quote-based for enterprise customers, indicating a tiered or negotiated subscription structure.
2. Usage-Based Expansion: Pricing inquiry form asks about cluster count (1-3, 4-10, 10+) and workloads per cluster, suggesting consumption-based expansion as organizations scale their Kubernetes footprint across more clusters and workloads.

Pricing tiers

Go-to-market motion3 records

Distribution channels4 records

Marketing channels6 records

Core offering

ScaleOps provides an autonomous Kubernetes resource management and cost optimization platform that continuously analyzes live workload behavior and dynamically adjusts CPU, memory, GPU, storage, and networking requests in real time. The platform is designed to coexist with existing Kubernetes tooling (HPA, KEDA, Karpenter) and supports deployment as a self-hosted, cloud-managed, or air-gapped instance.

Product overview

ScaleOps offers a unified autonomous Kubernetes resource management platform that provides real-time, context-aware automation for CPU, memory, GPU, storage, and network resources. The platform consists of core infrastructure optimization products (Automated Pod Rightsizing, Replica Optimization, Smart Pod Placement, Spot Optimization, Node Optimization, Karpenter Optimization, Java Resource Management), a dedicated GPU Optimization suite (Automated Fractional GPUs, GPU Memory Optimization, AI Replica Optimization, Batch Inference Optimization, AI Inference Observability), and observability tools (Cost Monitoring, Cluster and Workload Troubleshooting). Supporting technologies include an AI SRE Agent for intelligent cluster investigation and multiple deployment options (Self-Hosted, ScaleOps Cloud, Air-Gapped). The platform is designed for enterprises managing complex Kubernetes environments, particularly those running AI/ML workloads with GPU requirements.

Differentiator

Problem solved

Functional benefit

Brands

• AI SRE Agent: Context-aware monitoring and optimization tool for production Kubernetes clusters that interprets metrics with workload history to improve autoscaling and resource allocation decisions.

Products and services

• Automated Real-Time Pod Rightsizing Continuously analyzes live pod behavior and dynamically adjusts CPU and memory requests in real time to eliminate over-provisioning and reduce cloud waste.
• Replica Optimization
• Smart Pod Placement
• Spot Optimization
• Node Optimization
• Karpenter Optimization
• Java Resource Management
• Automated Fractional GPUs Dynamically shares and allocates fractional GPU resources across workloads to maximize GPU utilization and reduce AI infrastructure cost.
• GPU Memory Optimization
• AI Replica Optimization
• Batch Inference Optimization
• AI Inference Observability
• Kubernetes Cost Monitoring
• Cluster and Workload Troubleshooting
• AI SRE Agent An AI-powered SRE agent that assists platform teams with cluster operations, troubleshooting, and remediation using retrieval-augmented generation over operational data.
• Self-Hosted Deployment
• ScaleOps Cloud
• Air-Gapped Deployment
• AI Infrastructure Product Suite A unified suite of AI-specific infrastructure optimization capabilities covering GPU allocation, GPU memory, replica tuning, batch inference, and AI inference observability.

Quantifiable outcome

• Up to 80% reduction in Kubernetes resource costs
• +5 more outcomes

Named customers24 records

Segments3 records

Ideal customer profiles2 records

Technology focussed Yes

API detail

Has API

No

API docs

API detail

Core technology

AI maturity

App detail

Integration4 records

AI capability7 records

Feature16 records

Partnerships

Six partnerships are on record, tiered core.

• Amazon Web Services (AWS)coreTechnology or IntegrationScaleOps is available on AWS Marketplace and provides native integration with EKS (Elastic Kubernetes Service). The platform optimizes AWS EC2 instance selection and integrates with AWS cost management tools.
• Microsoft AzurecoreTechnology or IntegrationScaleOps is available on Azure Marketplace and provides native integration with AKS (Azure Kubernetes Service).
• Google Cloud Platform (GCP)coreTechnology or IntegrationScaleOps is available on Google Cloud Marketplace and provides native integration with GKE (Google Kubernetes Engine).
• KarpentercoreTechnology or IntegrationScaleOps provides specialized Karpenter Optimization that enhances Karpenter's instance selection, disruption budgets, and identifies inefficiencies without requiring changes to existing setup.
• Kubernetes HPA and KEDAcoreTechnology or IntegrationScaleOps runs alongside Horizontal Pod Autoscaler (HPA) and KEDA with no configuration required, coordinating vertical and horizontal scaling without conflicts.
• CNCF (Cloud Native Computing Foundation)coreTechnology or IntegrationScaleOps is a proud member of CNCF and a Diamond Sponsor at KubeCon North America 2026.

Scale indicators15 records

Recent moves6 records

Expansion highlights7 records

Broad incumbents

• Morpheus (HPE): Morpheus by HPE delivers multi-cloud application and infrastructure management including Kubernetes orchestration with cost and resource optimization, overlapping with ScaleOps as part of a broader hybrid cloud platform.
• Apptio (IBM): Apptio, an IBM company, is a leading enterprise cloud FinOps and IT financial management platform serving large enterprises. It is regularly evaluated by the same CIO/FinOps buyer as ScaleOps, though it is broader and less K8s-specialized.
• Harness: Harness provides a unified DevOps platform with built-in cloud cost management and continuous delivery. Its cloud cost management module competes broadly with ScaleOps as part of a larger CI/CD and FinOps suite.

Direct peers

• Vantage: Vantage specializes in cloud cost observability with strong Kubernetes support and AI workload cost analytics, overlapping with ScaleOps on K8s cost monitoring and emerging GPU cost use cases.
• Spot.io (NetApp): Spot by NetApp offers cloud infrastructure optimization including continuous K8s rightsizing, spot instance automation, and cost analytics—closely mirroring ScaleOps' product surface across automated scaling and cost reduction.
• Densify: Densify offers cloud and container resource optimization with predictive analytics for Kubernetes and VM environments, addressing the same rightsizing and FinOps use cases as ScaleOps.
• Kubecost: Kubecost provides Kubernetes cost monitoring, allocation, and optimization recommendations. Acquired by Cisco, it remains a leading K8s cost observability and rightsizing competitor in the same buyer evaluation.
• StormForge: StormForge delivers Kubernetes resource optimization and automated cloud cost management with machine learning-driven right-sizing for production clusters—competing head-to-head with ScaleOps in autonomous K8s optimization.
• CAST AI: CAST AI provides autonomous Kubernetes cost optimization and security, including automated rightsizing, spot instance management, and node optimization—directly overlapping with ScaleOps' core platform across CPU, memory, and GPU workloads.
• CloudZero: CloudZero provides cloud cost management with deep Kubernetes cost allocation and optimization capabilities, frequently evaluated alongside ScaleOps by FinOps and platform engineering teams.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat5 records

Key risks5 records

Key highlights7 records

Customer concentration

• LinkedInlinkedin.com/company/scaleops-sh

Compliance1 record

Revenue estimate

Valuation estimate

Number of profiles

Profiles3 records

Funding overview

Funding rounds5 records

Investors6 records

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about ScaleOps