Elotl
- Company typePrivate
- Founded2016
- HeadquartersSan Francisco, United States
- Headcount1–10
- GTM typeB2B
- OfferingSoftware
Elotl firmographics
Firmographics- Name
- Elotl
- Legal name
- Elotl, Inc.
- Website
- https://elotl.co
- Company type
- Private
- Founded year
- 2016
- Operating status
- Operating
- Headcount range
- 1–10 employees
- Ownership category
- akta.pro rank
Elotl industry classification
Industry- Product category
- AI Infrastructure Software
- NAICS
- Computer Systems Design and Related Services (5415)
- SIC
- Services-Prepackaged Software (7372)
- akta.pro primary industry
- End-to-End Enterprise AI Platforms (MLOps & Model Lifecycle Management) (HDAEANAA)
- akta.pro secondary industries
- Model Serving, Inference & Deployment Platforms (APIs, Edge/On-Prem) (HDAEANAC), AI Observability, Monitoring & Evaluation Platforms (Drift, Quality, Safety) (HDAEANAF)
Keywords
Where Elotl is headquartered
LocationHeadquarters
- HQ city
- San Francisco
- HQ country
- United States
- HQ region
- North America
Offices1 record
Markets served
Elotl business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Marketing or Sales, Operations, Infrastructure
Revenue model
- Software Licenses / Subscriptions: Elotl generates revenue through software licensing of Luna and Nova products. Both products are available as trial versions (free with limitations) and full versions for enterprise use. The company likely offers subscription-based pricing for its enterprise products, given the technical product complexity and enterprise sales motion.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Freemium | Pay-as-you-go | Nova Free Trial - fully operational with limitation of 6 workload clusters |
| Freemium | Pay-as-you-go | Luna Free Trial - fully operational with limitation of 10 concurrent nodes |
Go-to-market motion2 records
Distribution channels1 record
Marketing channels7 records
Elotl product offering
Product offeringCore offering
Elotl provides an AI Infrastructure Engine for the multi-cloud era, consisting of two Kubernetes-native products: Luna, a machine-learning-powered compute cluster autoscaler that intelligently rightsizes resources for AI workloads, and Nova, a policy-driven multi-cluster orchestrator that spans on-premises, hyperscalers, and neoclouds. Together they enable enterprise AI platform teams to schedule, scale, and govern AI workloads across heterogeneous infrastructure with policy-based placement and cost optimization.
Product overview
Elotl provides an AI Infrastructure Engine for the multi-cloud era, consisting of two core products: Nova (policy-driven multi-cluster orchestrator) and Luna (intelligent cluster autoscaler). Nova manages Kubernetes clusters across on-prem, hyperscalers, and neoclouds, enabling enterprises to schedule AI workloads like Ray and PyTorch as a single logical compute fabric. Luna provisions just-in-time, right-sized compute for AI/ML workloads, reducing GPU costs. The products work together: Nova performs fleet-level workload placement and scheduling, while Luna handles node-level autoscaling with GPU awareness and cost optimization. Additional offerings include SkyRay (KubeRay multi-cluster extension), SuperSkyRay (cross-cluster Ray with Cilium Cluster Mesh), and Thrifty-Nova (cost-ordered workload placement).
Differentiator
Problem solved
Functional benefit
Brands
- Luna: An Intelligent Compute Cluster Autoscaler that provisions just-in-time, right-sized, and cost-effective compute for Kubernetes workloads. Reduces operational complexity and prevents wasted spend for dynamic and bursty workloads including AI/ML Training, Serving, and Batch workloads.
- Nova
Products and services
- Luna An intelligent compute cluster autoscaler for Kubernetes that uses machine learning to predict pod requirements, optimize GPU node selection, and rightsize resources for AI workloads. It is positioned as a drop-in replacement for the standard Kubernetes cluster-autoscaler and is intended for enterprise AI platform teams running GPU-intensive workloads across AWS, Azure, GCP, and on-premises environments.
- Nova A policy-driven multi-cluster Kubernetes orchestrator that provides a single API and policy engine to manage AI workloads across heterogeneous infrastructure, including on-premises data centers, hyperscalers, and neoclouds. It enables centralized workload placement, multi-tenancy with RBAC, spreading across failure domains, and cost-aware deployment targeting.
- Thrifty-Nova A cost-efficient, multi-cluster orchestrator for AI training workloads, positioned as a variant of Nova that prioritizes cost optimization across heterogeneous infrastructure. It is designed for enterprises seeking to reduce GPU compute spend on training jobs running across hyperscalers, neoclouds, and on-premises environments.
Quantifiable outcome
- Up to 60% reduction in LLM deploy times on cloud Kubernetes with Luna
- +2 more outcomes
Companies that use Elotl
Customer profileNamed customers1 record
Segments2 records
Ideal customer profiles1 record
Elotl technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- No
- API docs
- API detail
Core technology
AI maturity
App detail
Integration15 records
AI capability4 records
Feature6 records
Elotl partnerships and signals
Strategic signalScale indicators2 records
Recent moves7 records
Expansion highlights6 records
Elotl competitors and assessment
Company assessmentEmerging players
- Anyscale: Anyscale is the commercial entity behind Ray and KubeRay, providing a managed platform for distributed AI workloads on Kubernetes. Overlaps with Elotl SkyRay/SuperSkyRay on multi-cluster Ray orchestration; serves as both a technology partner (Elotl integrates KubeRay) and a potential competitor in the AI workload orchestration space.
- ScaleOps: ScaleOps provides autonomous Kubernetes resource right-sizing and autoscaling, dynamically adjusting pod requests/limits in production. An emerging player with partial overlap to Elotl Luna's intelligent autoscaling and VPA integration; focuses more on pod-level optimization than cluster-level GPU sourcing.
Direct peers
- Spot.io (Spot by NetApp): Spot.io (now part of NetApp) provides Kubernetes cost optimization through spot instances, autoscaling, and infrastructure orchestration. Directly comparable to Elotl's Luna autoscaler and Thrifty-Nova cost-ordered placement; both compete on Elastigroup-style spot orchestration and multi-cloud scheduling for K8s workloads.
- Rafay Systems: Rafay provides a Kubernetes management platform with multi-cluster orchestration, policy-based workload placement, and GPU support for AI workloads. Directly comparable to Elotl Nova's policy-driven multi-cluster orchestration and fleet management capabilities, serving similar enterprise platform team buyers.
- StormForge: StormForge provides Kubernetes cost optimization and autoscaling with ML-driven recommendations for resource right-sizing. Comparable to Elotl Luna's intelligent autoscaling and VPA integration; both target cost reduction for production K8s workloads including AI/ML use cases.
- Spectro Cloud: Spectro Cloud offers enterprise Kubernetes management with multi-cluster orchestration, GPU support, and policy-driven workload placement across cloud and edge. Comparable to Elotl Nova's multi-cluster fleet management; both target enterprise platform teams running AI workloads across distributed K8s environments.
- Cast AI: Cast AI provides automated Kubernetes cost optimization and autoscaling across AWS, GCP, Azure, and on-prem. Directly comparable to Elotl Luna as a Kubernetes-native autoscaler focused on cost reduction, with similar bin-packing and spot instance optimization features. Both target the same buyer persona of platform teams running AI/general workloads on Kubernetes.
Others
- CoreWeave: CoreWeave is a GPU-specialized neocloud provider explicitly listed as supported by Elotl Nova. Functionally an ecosystem partner/upstream provider rather than a direct competitor, but represents the type of GPU cloud vendor whose pricing and capacity dynamics directly affect Elotl's value proposition to customers.
Broad incumbents
- Google GKE Autopilot: Google's GKE Autopilot is a managed Kubernetes mode that automates node management, autoscaling, and resource optimization. A broad incumbent competing with Elotl Luna on GCP, providing automated autoscaling out-of-the-box as part of the managed GKE service.
- AWS Karpenter: Karpenter is AWS's open-source Kubernetes autoscaler, now the default node provisioner for EKS Auto Mode. A broad incumbent competing directly with Elotl Luna on Kubernetes autoscaling within AWS; its bundling into EKS reduces the urgency of buying a third-party autoscaler for AWS-only deployments.
Market position
Strengths5 records
Weaknesses5 records
Competitive moat5 records
Key risks5 records
Key highlights6 records
Customer concentration
Elotl social profiles
Digital presenceElotl financial estimates
Financial estimateRevenue estimate
Valuation estimate
Elotl leadership team
Management profileNumber of profiles
Profiles6 records
Elotl funding detail
Funding detailFunding overview
Funding rounds4 records
Investors6 records
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
Elotl M&A and investment
M&A and investmentM&A
Investments
M&A and investment is available on the Subscription and Enterprise plan.Contact sales →
Frequently asked questions about Elotl
What does Elotl do?
Elotl provides an AI Infrastructure Engine for the multi-cloud era, consisting of two Kubernetes-native products: Luna, a machine-learning-powered compute cluster autoscaler that intelligently rightsizes resources for AI workloads, and Nova, a policy-driven multi-cluster orchestrator that spans on-premises, hyperscalers, and neoclouds. Together they enable enterprise AI platform teams to schedule, scale, and govern AI workloads across heterogeneous infrastructure with policy-based placement and cost optimization.
Is Elotl a public or private company?
Elotl is a private company. It is classified as venture growth investor backed and is currently operating.
When was Elotl founded?
Elotl was founded in 2016. It employs 1 to 10 people.
Where is Elotl based?
Elotl is headquartered in San Francisco, United States, in the North America region.
How does Elotl make money?
One revenue line is on record: software Licenses / Subscriptions.
Who are Elotl's main competitors?
Emerging players on record are Anyscale and ScaleOps. Direct peers are Spot.io (Spot by NetApp), Rafay Systems, StormForge, Spectro Cloud and Cast AI. CoreWeave is listed as an others. Broad incumbents are Google GKE Autopilot and AWS Karpenter.
Does Elotl have an API?
No public API is recorded for Elotl.
What industry is Elotl in?
Elotl's product category is AI Infrastructure Software. Its primary akta.pro industry code is HDAEANAA, End-to-End Enterprise AI Platforms (MLOps & Model Lifecycle Management), with a secondary code of HDAEANAC, Model Serving, Inference & Deployment Platforms (APIs, Edge/On-Prem). Its NAICS code is 5415 and its SIC code is 7372.