KitOps
- Company typePrivate
- Founded-
- Headquarters—
- Headcount1–10
- GTM typeB2B
- OfferingSoftware
What KitOps does
KitOps is an open source AI/ML artifact packaging project operating under the Linux Foundation as a Series of LF Projects, LLC. Its core technology bundles models, datasets, code, MCP servers, agent skills, guardrail configs, and policies into single versioned OCI artifacts (called ModelKits) that are stored in standard container registries and signed with Cosign using SHA-256 hashing for tamper-evidence. The platform is delivered through the Kit CLI (Docker-like commands: kit pack, push, pull, tag), the PyKitOps Python SDK, and a GitHub Action for CI/CD automation, with native integrations to MLflow, Kubeflow, KServe, and all major OCI-compliant registries (Docker Hub, ECR, GCR, Harbor, Artifactory, Jozu Hub). KitOps is the reference implementation of the CNCF ModelPack specification, formalized in 2024 with contributions from Red Hat, PayPal, ANTGroup, and ByteDance, and generates AI Bills of Materials mapped to EU AI Act and NIST AI RMF requirements.
The project serves enterprise AI/ML teams that need to package, version, sign, and govern AI artifacts across handoffs between data science, application, and deployment teams. It has accumulated 260,000+ downloads and 18+ months of production usage, and is licensed under Apache 2.0. The organization employs 1-10 people. Commercial monetization is indirect: enterprise support, vulnerability scanning, and policy-gated promotion are sold through Jozu, which operates as KitOps' primary commercial partner and offers quote-based enterprise support plans. There are no disclosed funding rounds, named enterprise customers, or revenue figures in the source material, indicating the project is community-governed rather than venture-backed.
KitOps firmographics
Firmographics- Name
- KitOps
- Legal name
- KitOps a Series of LF Projects, LLC
- Website
- https://kitops.ml
- Company type
- Private
- Operating status
- Operating
- Headcount range
- 1–10 employees
- Ownership category
- akta.pro rank
KitOps industry classification
Industry- Product category
- AI/ML Artifact Packaging & MLOps Software
- NAICS
- Software Publishers (5132), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (51821)
- SIC
- Services-Prepackaged Software (7372), Services-Computer Integrated Systems Design (7373)
- akta.pro primary industry
- End-to-End MLOps & ML Platform Suites (HDAAABAA)
- akta.pro secondary industries
- Container Runtime & Image Infrastructure (HDABADAG), Experiment Tracking, Metadata & Model Registry (HDAAABAC), Software Supply Chain & Dependency Security (SBOM, Signing) (HDADACAD), Platform Engineering & Internal Developer Platforms (IDP) (BPAEAKAC)
Keywords
KitOps business model
Business model- GTM type
- B2B
- Offering type
- Software
- Cost components
- Personnel, Technology or R&D, Operations, Marketing or Sales, Infrastructure
Revenue model
- Open Source Core (Apache 2.0): The KitOps CLI, Python SDK, and ModelKit format are open source under Apache 2.0 license, freely available for all users and contributors.
- Enterprise Support (via Jozu): Jozu provides production-ready enterprise support for KitOps ModelKits and CLI, including professional support plans for organizations requiring SLA guarantees, troubleshooting assistance, and dedicated support.
Pricing tiers
| Model | Billing | Price |
|---|---|---|
| Freemium | Others | Open Source - Free |
Go-to-market motion2 records
Distribution channels3 records
Marketing channels4 records
KitOps product offering
Product offeringCore offering
KitOps packages AI/ML artifacts — including models, datasets, code, MCP servers, agent skills, guardrail configs, and policies — as versioned, cryptographically signed OCI artifacts (called ModelKits) that are stored in standard OCI-compliant container registries. The platform is delivered through an open source Kit CLI (Docker-like kit pack/push/pull/tag commands), a PyKitOps Python SDK, and a CI/CD GitHub Action, and it serves as the reference implementation of the CNCF ModelPack specification. Enterprise-grade support, vulnerability scanning, and policy-gated promotion are provided through the strategic partner Jozu.
Product overview
KitOps is a unified AI packaging and versioning platform built around ModelKits — OCI-compliant artifacts that bundle models, datasets, code, agent skills, MCP servers, guardrail configs, and policies into single immutable, cryptographically-signed packages. The core platform consists of the Kit CLI (command-line interface), PyKitOps (Python SDK), and KitOps GitHub Action (CI/CD integration) that work together to enable standardized AI artifact management across the ML development lifecycle. KitOps serves as the reference implementation of the CNCF ModelPack specification and integrates with enterprise tools like Jozu Hub for vulnerability scanning and Kubeflow/KServe for orchestration and serving.
Differentiator
Problem solved
Functional benefit
Brands
- ModelKits: Versioned OCI artifacts that bundle models, datasets, code, agent skills, MCP servers, guardrail configs, and policies into a single shareable package.
- Kit CLI
- PyKitOps
Products and services
- ModelKits Versioned, signed OCI artifacts that bundle models, datasets, code, agent skills, MCP servers, guardrail configs, and policies into a single tamper-evident package for AI supply chain management. Targeted at enterprise AI/ML teams handing artifacts between data science, application, and deployment teams.
- Kit CLI Command-line interface for packaging, pushing, pulling, and tagging ModelKits using Docker-mirroring commands (kit pack, push, pull, tag). Targeted at engineers and ML/MLOps practitioners.
- PyKitOps Python SDK Python SDK for building and managing ModelKits directly from Python code, enabling integration into existing ML pipelines and tools such as MLflow without rewriting workflows. Targeted at Python-based ML/MLOps developers.
- KitOps GitHub Action CI/CD integration action that automates ModelKit packaging on every commit and pushes packages to registries with policy gating for promotions. Targeted at engineering teams using GitHub Actions for CI/CD.
Companies that use KitOps
Customer profileSegments1 record
Ideal customer profiles2 records
KitOps technology and API
TechnologyTechnology focussed Yes
API detail
- Has API
- No
- API docs
- API detail
Core technology
AI maturity
App detail
Integration15 records
AI capability2 records
Feature7 records
KitOps partnerships and signals
Strategic signalPartnerships
Six partnerships are on record, tiered core and flagship.
- JozucoreJozu is the primary commercial partner for KitOps, providing production-ready enterprise support and professional support plans. Jozu Hub is also offered as a registry option for storing ModelKits alongside other OCI-compliant registries.
- CNCF (Cloud Native Computing Foundation)coreKitOps is a CNCF project and the reference implementation of the ModelPack specification. The specification was formalized with contributions from Jozu, Red Hat, PayPal, ANTGroup, and ByteDance. CNCF governance ensures vendor neutrality and an enterprise ML standard.
- MLflowflagshipKitOps integrates with MLflow through the PyKitOps SDK, allowing teams to build and manage ModelKits within MLflow pipelines without rewriting existing workflows.
- KubeflowcoreKitOps integrates with Kubeflow pipelines for AI/ML workflow orchestration, enabling ModelKits to be used within Kubeflow-powered ML pipelines.
- KServecoreKitOps serves models directly to KServe via kit:// URIs, enabling seamless model deployment from ModelKits to KServe inference service.
- GitHub ActionsflagshipOfficial KitOps GitHub Action enables automated packaging of ModelKits on every commit, pushing to registries with policy gating for promotions. Published on GitHub Marketplace.
Scale indicators2 records
Recent moves6 records
Expansion highlights5 records
KitOps competitors and assessment
Company assessmentBroad incumbents
- Docker: Docker created the container image format and OCI standard that KitOps builds on. While not a direct packaging competitor for AI artifacts, Docker's broader developer ecosystem and registry (Docker Hub) overlap with KitOps' distribution surface.
- MLflow (Databricks): MLflow provides an end-to-end open source MLOps platform including a native model registry, experiment tracking, and packaging. KitOps integrates with MLflow but its model versioning and packaging overlap with MLflow's registry, positioning MLflow as both partner and competitor.
- Weights & Biases: Weights & Biases offers an end-to-end MLOps platform with experiment tracking, model registry, and artifact management. Its model and artifact registry overlap with KitOps' ModelKit packaging, though W&B is a proprietary platform rather than an OCI-based open standard.
Direct peers
- Jozu: Jozu is both KitOps' primary commercial partner and a direct competitor in the KitOps ecosystem: it offers enterprise support, vulnerability scanning, and policy-gated promotion on top of ModelKits, and runs Jozu Hub as an OCI registry option.
- BentoML: BentoML packages ML models into reproducible, deployable artifacts for serving. Like KitOps, it focuses on standardizing model packaging, though BentoML emphasizes the serving-side bundle rather than OCI-native distribution across heterogeneous registries.
- Hugging Face: Hugging Face Hub is the dominant destination for sharing and versioning models, datasets, and Spaces. It competes directly with KitOps' mission of standardizing AI artifact distribution, though with a proprietary rather than OCI-based format.
- Pachyderm: Pachyderm provides data versioning and pipeline orchestration for ML, addressing reproducibility and provenance of datasets and models. It competes with KitOps' versioning and governance value proposition, particularly in regulated and enterprise data workflows.
- Iterative (DVC): DVC and Iterative Studio provide data and model versioning for ML projects, addressing the same problem KitOps solves but using Git-based workflows rather than OCI artifacts. They overlap in value proposition (versioning, reproducibility, governance).
Market position
Strengths4 records
Weaknesses4 records
Competitive moat4 records
Key risks6 records
Key highlights7 records
Customer concentration
KitOps social profiles
Digital presenceKitOps compliance and trust
Trust signalCompliance2 records
KitOps financial estimates
Financial estimateRevenue estimate
Valuation estimate
KitOps leadership team
Management profileNumber of profiles
KitOps funding detail
Funding detailFunding overview
Funding rounds
Investors
Funding detail is available on the Subscription and Enterprise plan.Contact sales →
KitOps 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 KitOps
What does KitOps do?
KitOps packages AI/ML artifacts — including models, datasets, code, MCP servers, agent skills, guardrail configs, and policies — as versioned, cryptographically signed OCI artifacts (called ModelKits) that are stored in standard OCI-compliant container registries. The platform is delivered through an open source Kit CLI (Docker-like kit pack/push/pull/tag commands), a PyKitOps Python SDK, and a CI/CD GitHub Action, and it serves as the reference implementation of the CNCF ModelPack specification. Enterprise-grade support, vulnerability scanning, and policy-gated promotion are provided through the strategic partner Jozu.
Is KitOps a public or private company?
KitOps is a private company. It is classified as nonprofit foundation owned and is currently operating.
When was KitOps founded?
KitOps was founded in -1. It employs 1 to 10 people.
How does KitOps make money?
Two revenue lines are on record. Open Source Core (Apache 2.0) is the primary driver. The others are enterprise Support (via Jozu).
Who are KitOps's main competitors?
Broad incumbents on record are Docker, MLflow (Databricks) and Weights & Biases. Direct peers are Jozu, BentoML, Hugging Face, Pachyderm and Iterative (DVC).
Does KitOps have an API?
No public API is recorded for KitOps.
What industry is KitOps in?
KitOps's product category is AI/ML Artifact Packaging & MLOps Software. Its primary akta.pro industry code is HDAAABAA, End-to-End MLOps & ML Platform Suites, with a secondary code of HDABADAG, Container Runtime & Image Infrastructure. Its NAICS code is 5132 and its SIC code is 7372.