Neptune.ai

Neptune.ai is an experiment tracker for ML and foundation-model training. As of 2025, Neptune.ai is being acquired by OpenAI and the public pricing page redirects to the OpenAI announcement. Customers continue to use the Neptune Python client and REST API during the transition.

Neptune.ai is listed with 2 APIs on the APIs.io network. Tagged areas include Machine Learning, MLOps, Experiment Tracking, Foundation Models, and Acquired.

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16.0/100 emerging ▬ flat Agent 1/100 human only open core · Apache-2.0 Full breakdown ↓
scored 2026-11-13 · rubric v0.28.0 · Show this score on your site →

AccessEnterprise

2 APIs

Machine Learning MLOps Experiment Tracking Foundation Models Acquired

Kin Score

Kin Score How this is scored →
scored 2026-11-13 · rubric v0.28.0

Composite quality — 16.0/100 · emerging

Contract Quality 0.0 / 19

Developer Ergonomics 1.8 / 15

Access Clarity 1.6 / 15

Operational Transparency 3.2 / 10

Contract Governance 0.0 / 9

Discoverability 5.0 / 8

Regulatory Posture 0.8 / 15

Open Source Surface 4.0 / 10

Agent readiness — 1/100 · human only

Machine-Readable Contract 0 / 18

Agentic Access Contract 0 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 12

Machine-Readable Auth 0 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 7 / 7

Typed Event Surface 0 / 6

Agent Skills 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Well-Known Document 0 / 5

Pagination 5 / 5

Distinct Operations 3 / 3

MCP Tool Quality 6 / 6

Regulatory Posture applies to this provider. Its tags matched the AI & Biometrics regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.

Open Source Surface applies to this provider. This product is open source and we read its repository directly, so Open Source Surface carries 10 points of the composite. It is scored from what the repository actually publishes — a security policy, a contribution guide, a release history, a code of conduct — read live from the provider rather than inferred from our own catalog pointers. This facet adds; nothing was taken away to make room for it. An open-source project is not excused from the commercial facets, because exemption would strip it of the points it does earn. If we have the wrong repository, or this product is not open source, say so on your provider repo and we will drop the facet rather than have you publish against it.

Create-or-Update Ergonomics could not be measured. We hold no machine-readable contract for this provider to read, so there is nothing to measure a write surface against. Excluded rather than scored zero: never-measured and measured-empty are different facts. Publishing an OpenAPI is what makes this facet — and several others — scorable at all.

The six quality facets above are damped to 75 points between them, because both conditional facets apply and carry 25 points together. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 75% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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Agent readiness — checks not met, largest first (exact, from this profile):

Machine-Readable Contract +18 pts — api_specs includes an OpenAPI document Ask about this →
MCP Server +12 pts — deployment.mode + probe verdict on the mcp/ manifest, not the pointer; an unprobed slug falls back to authorship Ask about this →
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author Ask about this →
Machine-Readable Auth +10 pts — a served openid-configuration/oauth-authorization-server carrying `issuer` (served), else the securitySchemes class in the provider OpenAPIs — bound (mutualTLS, DPoP, Signature) > negotiable (oauth2 authorizationCode/clientCredentials, openIdConnect) > bearer (http bearer, apiKey) Ask about this →
Idempotency +9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented) Ask about this →
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes Ask about this →

12 more unmet checks in the Agent Readiness table above.

Kin Score — facets with the most composite points still available (weight × headroom):

Contract Quality scores 0.0 — up to +25.0 composite points Ask about this →
Access Clarity scores 10.6 — up to +17.9 composite points Ask about this →
Developer Ergonomics scores 11.9 — up to +17.6 composite points Ask about this →

Each check links to what satisfies it. Publish the artifact, or tell us where it already lives, and the score moves on the next scoring run.

Not sure how this applies to your stack? Ask about any one item. Kin Lane reads every question, looks at your profile and your situation, and replies with what a fix would take — scoped to that one area, priced up front, yours whether you ship it or not. Ask a question →

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. Every facet and dimension name above is a link: it opens that measurement's own page — what it means, the exact checks that feed it, how the whole catalog distributes on it, and the providers at the top of it. This rating is computed from the provider profile at artifacts.apis.io/neptune-ai/apis.yml: open an issue on github.com/api-evangelist/neptune-ai to ask a question or point us at an artifact you publish. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Markets this provider is in provisional

The Kin Score Market layer reads a provider inside its market: its position, and how deep its integrations go. Depth is only comparable within a position. Provisional and unweighted: not part of the Kin Score or agent readiness.

Market	Position	Depth	Registered MCP server	Declares compatibility
MLOps and AI/ML Infrastructure (LF AI & Data, MLPerf, Kubeflow)	builds-on	17.2 (thin)	-	-

Registered MCP server and declares compatibility are report only — not weighted. Undeclared means we found nothing we can read, so there is no number: we never infer integrations.

APIs 2

Individual APIs this provider publishes, each with its own machine-readable definition.

Neptune.ai REST API

The Neptune REST API backs the Neptune Python client. It exposes runs, projects, fields, and metadata logging. Authentication uses an API token from the user profile.

Neptune Scale API (foundation-model tier)

Neptune Scale is the higher-throughput logging surface designed for foundation model training jobs. Same API-token authentication; SDK support in `neptune-scale`.

Neptune.ai API pricing

Not yet checked against Neptune.ai's own pricing page. Compiled by API Evangelist on 2026-05-08 from neptune.ai/; confirm before you rely on a figure.

Plan	Price
To Be Reconciled enterprise	—

Plan details, limits and sources →

Rate limits

Default: see provider documentation varies

Compiled by API Evangelist, not yet checked against Neptune.ai's documentation. Rate-limit details →

Pricing Plans 1

Published pricing tiers and plan structures.

Neptune.ai Plans Pricing

1 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Neptune.ai Rate Limits

1 limits

RATE LIMITS

Terms of Service 1

What its API terms permit and prohibit, quoted from its own page.

Neptune.ai

5 quoted statements, read from Neptune.ai's own page on 2026-11-10.

TERMS

Data License 1

How its data and outputs may be reused, quoted from its own terms.

Neptune.ai

2 quoted statements, read from Neptune.ai's own page on 2026-11-10.

LICENSE

FinOps 1

Cost, billing, and metering signals for API financial operations.

Neptune.ai Finops

FINOPS

Security Posture 1

Authentication, domain security, vulnerability disclosure, and trust-center signals.

Neptune.ai Domain Security

TLSv1.3 · HSTS · DNSSEC · DMARC

SECURITY

Resources

Build 2

SDKs, sample code, and the tooling you integrate with

CodeOfConduct

CodeOfConduct

neptune client

SourceCode

Access & Security 2

Authentication, authorization, and security posture

SecurityPolicy

SecurityPolicy

DomainSecurity

DomainSecurity

Operate 3

Status, limits, changes, and where to get help

IssueTracker

IssueTracker

Releases

Releases

RateLimits

RateLimits

Commercial 5

Pricing, plans, and the legal terms of use

License

Plans

FinOps

UsageTerms

DataLicense

Company 2

The organization behind the API

LinkedIn

Website

Website

Other 1

Properties that don't map to a standard resource type

Acquisition

Acquisition

Source (apis.yml)

aid: neptune-ai
url: https://raw.githubusercontent.com/api-evangelist/neptune-ai/refs/heads/main/apis.yml
name: Neptune.ai
kind: company
description: Neptune.ai is an experiment tracker for ML and foundation-model training. As of 2025, Neptune.ai is being acquired
  by OpenAI and the public pricing page redirects to the OpenAI announcement. Customers continue to use the Neptune Python
  client and REST API during the transition.
deliveryModel:
  model: open-core
  license: Apache-2.0
  open_source: true
  commercial: true
  callable_host: false
  label: Open core · an OSS project plus a commercial hosted product
  confidence: high
  source:
  - license
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: enterprise
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Enterprise
  confidence: low
  source:
  - plans
  - security
  generated: '2026-11-13'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/neptune-ai.png
tags:
- Machine Learning
- MLOps
- Experiment Tracking
- Foundation Models
- Acquired
tags_raw:
- ML
- MLOps
- Experiment Tracking
- Foundation Models
- Acquired
- Machine-Learning
created: '2026-05-08'
modified: '2026-05-08'
specificationVersion: '0.23'
apis:
- aid: neptune-ai:neptune-rest-api
  name: Neptune.ai REST API
  humanURL: https://docs-legacy.neptune.ai/api/api_reference/
  baseURL: https://app.neptune.ai/api
  tags:
  - REST
  - Runs
  - Project
  - Metrics
  tags_raw:
  - REST
  - Runs
  - Projects
  - Metrics
  description: The Neptune REST API backs the Neptune Python client. It exposes runs, projects, fields, and metadata logging.
    Authentication uses an API token from the user profile.
  properties:
  - type: Documentation
    url: https://docs-legacy.neptune.ai/api/api_reference/
  - type: SDKs
    title: Python (neptune)
    url: https://docs-legacy.neptune.ai/api/neptune/
- aid: neptune-ai:neptune-scale-api
  name: Neptune Scale API (foundation-model tier)
  humanURL: https://neptune.ai/docs
  baseURL: https://api.neptune.ai
  tags:
  - REST
  - Foundation Models
  - Scale
  description: Neptune Scale is the higher-throughput logging surface designed for foundation model training jobs. Same API-token
    authentication; SDK support in `neptune-scale`.
  properties:
  - type: Documentation
    url: https://neptune.ai/docs
common:
- type: IssueTracker
  url: https://github.com/neptune-ai/neptune-client/issues
- type: Releases
  url: https://github.com/neptune-ai/neptune-client/releases
- type: SecurityPolicy
  url: https://github.com/neptune-ai/neptune-client/blob/master/.github/SECURITY.md
- type: CodeOfConduct
  url: https://github.com/neptune-ai/neptune-client/blob/master/CODE_OF_CONDUCT.md
- type: License
  name: Apache-2.0
  url: https://github.com/neptune-ai/neptune-client/blob/master/LICENSE
- type: DomainSecurity
  url: security/neptune-ai-domain-security.yml
- type: LinkedIn
  url: https://www.linkedin.com/company/neptuneai
- type: Website
  url: https://neptune.ai/
- type: Acquisition
  url: https://openai.com/index/openai-to-acquire-neptune/
- type: SourceCode
  title: neptune client
  url: https://github.com/neptune-ai/neptune-client
- type: Plans
  url: plans/neptune-ai-plans-pricing.yml
- type: RateLimits
  url: rate-limits/neptune-ai-rate-limits.yml
- type: FinOps
  url: finops/neptune-ai-finops.yml
- type: UsageTerms
  url: terms/neptune-ai-terms-of-service.yml
- type: DataLicense
  url: data-license/neptune-ai-data-license.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com

Neptune.ai API — frequently asked questions

Does Neptune.ai have an API?

Yes. APIs.io lists 2 APIs from Neptune.ai, including Neptune.ai REST API and Neptune Scale API (foundation-model tier).

How much does the Neptune.ai API cost?

APIs.io lists 1 pricing plan for Neptune.ai, with each plan's price, limits and inclusions under Pricing on this page.

Is the Neptune.ai API ready for AI agents?

Neptune.ai has a Kin Score of 16.0 out of 100 (emerging) and an Agent Readiness score of 0.6 (human-only), scored by API Evangelist on 2026-11-13.

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