MLOps and AI/ML Infrastructure (LF AI & Data, MLPerf, Kubeflow)
Standards market (lf ai & data landscape + membership, mlperf benchmark results, kubeflow distributions). The Kin Score Market layer reads each provider in its market: who it integrates with, how deep those integrations go, and where the market publishes its own structure. Methodology.
Where this market publishes its structure
- LF AI & Data Landscape (lfai/landscape landscape.yml @95d361b8ab) machine-readable, 473 entries, 67 members, 40 hosting companies, 62 LF AI & Data projects; 69 providers linked
- MLCommons MLPerf results (mlcommons/*_results_v* repos: closed/ + open/ submitter directories) machine-readable, 54 round repos, 9 families (inference v6.1, training v6.0, storage v3.0, hpc v3.0, mobile, tiny, automotive, endpoints); 183 directories -> 118 organisations; 31 providers linked via Wikidata P856
- Kubeflow packaged distributions (kubeflow/website installing-kubeflow table @5a17330435) machine-readable, 6 rows; 1 linked (Red Hat); Canonical (ubuntu.com), prokube, QBO have no catalog holder; Azure/Nutanix link to github.io
- MLPerf AlgoPerf (algorithms_results) not machine-readable: anonymised team numbers, not organisations
- MLCommons members (mlcommons.org/our-members) not machine-readable: logo grid of images; no names or links in the HTML
- Hugging Face verified organisations not machine-readable: no public list; /api/organizations HTTP 401
- Ray ecosystem / integrations (docs.ray.io) not machine-readable: docs prose page, a mention list not a register
Own = declares at least one integration itself; covered = visible only because an aggregator, standards body, regulator or partner contract names it; distribution-only = listed only on cloud marketplaces it sells through, a channel reported beside, never counted as its own declared integrations; undeclared = nothing we can read, so no number; declares_compatibility = providers with a `compatible` shape vote, report only (kin, 2026-10-13): never counted as own, never in depth or position.
Taxonomy how this market maps onto apis.io
Derived 2026-10-21 from the 67 providers in this market we could resolve in the catalog. The percentage is the share of those providers carrying each one; it describes the market, not the tag or industry. Tag groups have no page of their own yet, so they are listed unlinked.
| Tags | MLOps 48%, Open Source 24%, Inference 21%, GPU 21% |
|---|---|
| Tag groups | MLOps 54%, LLM 43%, Hardware 22%, Kubernetes 21% |
| Industries | Artificial Intelligence 87%, Developer Tools & DevOps 40%, Semiconductors & Hardware 33% |
| Areas | Machine Learning 70% |
| Capabilities | Information & Data Management 42%, Cybersecurity Management 22% |
share of resolved cohort carrying it; tags >=0.20 & >=3 members (max 12, junk dropped), tag_groups >=0.20 (cooccurrence, non-cross-cutting; max 8), industries >=0.20 (max 6), areas >=0.10 (max 6; areas are keyword-matched and sparse), capabilities L1 >=0.20 (max 8); derive-market-taxonomy.py
Leaders by position (provisional)
Provisional: grouped by position, depth compared within a position only. Distribution (cloud marketplaces) and iPaaS bridges are counted beside position, never inside it. Unknown-builder listings are left out of position shares and counted here.
builds-on 12 · publishes apps on other platforms' stores
| Provider | Depth | Integrations | In / out | Unknown builder | Distribution | iPaaS bridge | Mix |
|---|---|---|---|---|---|---|---|
| Hewlett Packard Enterprise | 55.8 | 12 | 0 / 12 | 0 | 3 | 0 | standard 36%, builds-on-platform 43%, distribution 21% |
| JFrog | 51.8 | 14 | 0 / 14 | 0 | 1 | 0 | standard 14%, builds-on-platform 79%, distribution 7% |
| ZenML | 51.8 | 5 | 0 / 5 | 0 | 0 | 0 | standard 40%, builds-on-platform 60% |
| Paperspace | 51.7 | 3 | 0 / 3 | 0 | 0 | 0 | builds-on-platform 100% |
| Astronomer | 43.1 | 8 | 0 / 8 | 0 | 3 | 0 | builds-on-platform 62%, distribution 38% |
| DataRobot | 42.7 | 7 | 0 / 7 | 0 | 3 | 0 | contract 14%, builds-on-platform 43%, distribution 43% |
| TrueFoundry | 39.2 | 5 | 0 / 5 | 0 | 1 | 1 | ipaas-bridge 20%, standard 20%, builds-on-platform 40%, distribution 20% |
| Chalk | 32.6 | 6 | 0 / 6 | 0 | 5 | 0 | builds-on-platform 17%, distribution 83% |
| Dataiku | 29.2 | 4 | 0 / 4 | 0 | 4 | 1 | ipaas-bridge 17%, builds-on-platform 17%, distribution 67% |
| Roboflow | 25.5 | 6 | 0 / 6 | 0 | 4 | 2 | ipaas-bridge 29%, builds-on-platform 14%, distribution 57% |
| fiddler.ai | 17.2 thin | 1 | 0 / 1 | 0 | 0 | 0 | builds-on-platform 100% |
| Neptune.ai | 17.2 thin | 1 | 0 / 1 | 0 | 0 | 0 | builds-on-platform 100% |
covered 3 · reached mainly through aggregators
| Provider | Depth | Integrations | In / out | Unknown builder | Distribution | iPaaS bridge | Mix |
|---|---|---|---|---|---|---|---|
| Lambda | 51.7 | 3 | 0 / 3 | 0 | 0 | 0 | standard 33%, covered 67% |
| Modal | 41.9 | 7 | 0 / 7 | 0 | 3 | 0 | covered 29%, builds-on-platform 29%, distribution 43% |
| Segmind | 36.4 | 3 | 0 / 3 | 0 | 2 | 0 | covered 33%, distribution 67% |
standard 22 · listed by a voluntary standard's own directory
| Provider | Depth | Integrations | In / out | Unknown builder | Distribution | iPaaS bridge | Mix |
|---|---|---|---|---|---|---|---|
| Dell Technologies | 57.9 | 5 | 0 / 5 | 0 | 0 | 0 | standard 60%, builds-on-platform 40% |
| Qualcomm | 56.9 | 4 | 0 / 4 | 0 | 0 | 0 | standard 100% |
| CoreWeave | 53.5 | 8 | 0 / 8 | 0 | 0 | 0 | standard 62%, covered 12%, builds-on-platform 25% |
| Lenovo | 53.5 | 5 | 0 / 5 | 0 | 1 | 0 | standard 80%, distribution 20% |
| Intel | 53.4 | 12 | 0 / 12 | 0 | 0 | 0 | standard 75%, builds-on-platform 25% |
| MLflow | 52.4 | 3 | 0 / 3 | 0 | 0 | 0 | standard 100% |
| Labelbox | 51.7 | 3 | 0 / 3 | 0 | 0 | 0 | standard 67%, covered 33% |
| Advanced Micro Devices | 49.0 | 11 | 0 / 11 | 0 | 3 | 0 | standard 55%, builds-on-platform 18%, distribution 27% |
| Alluxio | 47.0 | 4 | 0 / 4 | 0 | 1 | 0 | standard 75%, distribution 25% |
| TensorFlow | 44.1 | 3 | 0 / 3 | 0 | 1 | 0 | standard 67%, distribution 33% |
| H2O.ai | 40.2 | 4 | 0 / 4 | 0 | 2 | 0 | standard 25%, builds-on-platform 25%, distribution 50% |
| FuriosaAI | 36.4 | 3 | 0 / 3 | 0 | 2 | 0 | standard 33%, distribution 67% |
| PyTorch | 34.5 thin | 2 | 0 / 2 | 0 | 0 | 0 | standard 100% |
| Seldon | 34.5 thin | 2 | 0 / 2 | 0 | 0 | 0 | standard 100% |
| Super Micro Computer | 19.8 thin | 1 | 0 / 1 | 0 | 0 | 0 | standard 100% |
| Determined AI | 17.2 thin | 1 | 0 / 1 | 0 | 0 | 0 | standard 100% |
| DVC | 17.2 thin | 1 | 0 / 1 | 0 | 0 | 0 | standard 100% |
| Flyte | 17.2 thin | 1 | 0 / 1 | 0 | 0 | 0 | standard 100% |
| Habana Labs | 17.2 thin | 1 | 0 / 1 | 0 | 0 | 0 | standard 100% |
| Kubeflow | 17.2 thin | 1 | 0 / 1 | 0 | 0 | 0 | standard 100% |
| Label Studio | 17.2 thin | 1 | 0 / 1 | 0 | 0 | 0 | standard 100% |
| Rebellions | 17.2 thin | 1 | 0 / 1 | 0 | 0 | 0 | standard 100% |
mixed 3 · no single mode dominates
| Provider | Depth | Integrations | In / out | Unknown builder | Distribution | iPaaS bridge | Mix |
|---|---|---|---|---|---|---|---|
| Weights and Biases | 51.7 | 3 | 0 / 3 | 0 | 0 | 0 | standard 33%, covered 33%, builds-on-platform 33% |
| Crusoe | 49.4 | 8 | 0 / 8 | 0 | 1 | 0 | standard 38%, covered 25%, builds-on-platform 25%, distribution 12% |
| SAKURA internet | 47.4 | 7 | 0 / 7 | 0 | 2 | 0 | contract 14%, standard 29%, builds-on-platform 29%, distribution 29% |
distribution 10 · only sells through cloud marketplaces
| Provider | Depth | Integrations | In / out | Unknown builder | Distribution | iPaaS bridge | Mix |
|---|---|---|---|---|---|---|---|
| Credo AI | 28.8 | 3 | 0 / 3 | 0 | 3 | 0 | distribution 100% |
| Edge Impulse | 28.8 | 3 | 0 / 3 | 0 | 4 | 0 | distribution 100% |
| ArthurAI | 19.2 thin | 2 | 0 / 2 | 0 | 2 | 0 | distribution 100% |
| Compresr | 19.2 thin | 2 | 0 / 2 | 0 | 2 | 0 | distribution 100% |
| DataLoop | 19.2 thin | 2 | 0 / 2 | 0 | 3 | 0 | distribution 100% |
| NexGen Cloud | 19.2 thin | 2 | 0 / 2 | 0 | 2 | 0 | distribution 100% |
| Tecton | 19.2 thin | 2 | 0 / 2 | 0 | 2 | 0 | distribution 100% |
| Comet | 9.6 thin | 1 | 0 / 1 | 0 | 1 | 0 | distribution 100% |
| Superb AI | 9.6 thin | 1 | 0 / 1 | 0 | 2 | 0 | distribution 100% |
| WhyLabs | 9.6 thin | 1 | 0 / 1 | 0 | 1 | 0 | distribution 100% |
undeclared 17 · declares nothing we can read: no number
| Provider | Depth | Integrations | In / out | Unknown builder | Distribution | iPaaS bridge | Mix |
|---|---|---|---|---|---|---|---|
| Arize AI | undeclared | - | - | - | - | - | |
| Chamber | undeclared | - | - | - | - | - | |
| ClearML | undeclared | - | - | - | - | - | |
| Domino Data Lab | undeclared | - | - | - | - | - | |
| Fiddler Labs | undeclared | - | - | - | - | - | |
| Hyperbolic | undeclared | - | - | - | - | - | |
| Inference | undeclared | - | - | - | - | - | |
| KServe | undeclared | - | - | - | - | - | |
| Azure Machine Learning | undeclared | - | - | - | - | - | |
| Mithril | undeclared | - | - | - | - | - | |
| Pachyderm | undeclared | - | - | - | - | - | |
| Probabl | undeclared | - | - | - | - | - | |
| Ray | undeclared | - | - | - | - | - | |
| RightNow AI | undeclared | - | - | - | - | - | |
| NVIDIA Run:ai | undeclared | - | - | - | - | - | |
| The San Francisco Compute Company | undeclared | - | - | - | - | - | |
| Weights & Biases | undeclared | - | - | - | - | - |
Generated 2026-10-21 from API Evangelist's own files; nothing on this page is a model's judgement. Provisional and unweighted; not part of the Kin Score composite or agent readiness. Read the Market layer methodology. Disagree with an edge? Every edge cites its evidence and can be corrected through the normal correction path.
