SigOpt

SigOpt was a machine learning experimentation and optimization platform whose API applied ensemble Bayesian and black-box optimization to tune model hyperparameters, run design-of-experiments, and track experiment metadata at scale. Developers integrated its REST API and first-party clients (Python, Java, R, scikit-learn, Spark, MATLAB) to drive automated hyperparameter search from their training loops. SigOpt was acquired by Intel in 2020 and its hosted API and platform were subsequently discontinued; sigopt.com now redirects to an Intel corporate redirector and the api./app./docs.sigopt.com hosts no longer resolve. The GitHub organization (github.com/sigopt) and the published client libraries remain public as historical, first-party artifacts, including an open-sourced server and optimization engine (sigopt-server, sigoptlite, libsigopt).

SigOpt is profiled on the APIs.io network. Tagged areas include Company, Machine Learning, Optimization, Hyperparameter Tuning, and Experimentation.

🌐 Visit website 📡 Source on GitHub

0.0/100 minimal Agent 0/100 human only Front door AI 2/6 trace library Full breakdown ↓
scored 2026-09-25 · rubric v0.23.0

0 APIs

Company Machine Learning OptimizationHyperparameter TuningExperimentationBayesian OptimizationMLOps Data Science Defunct

Kin Score

Kin Score How this is scored →
scored 2026-09-25 · rubric v0.23.0

Composite quality — 0.0/100 · minimal

Contract Quality 0.0 / 21

Developer Ergonomics 0.0 / 17

Access Clarity 0.0 / 17

Operational Transparency 0.0 / 11

Contract Governance 0.0 / 10

Discoverability 0.0 / 9

Regulatory Posture 0.0 / 15

Agent readiness — 0/100 · 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 0 / 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

Regulatory Posture applies to this provider. Its tags matched the Horizontal (data, software, accessibility, platform) 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.

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 85 points between them, because the conditional facet above carries the other 15. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 85% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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 github.com/api-evangelist/sigopt: open an issue to ask a question, or submit a pull request to add artifacts. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Resources

Build 4

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

SourceCode

Packages

SDKs

Company 1

The organization behind the API

Website

Website

Source (apis.yml)

aid: sigopt
deliveryModel:
  model: library
  open_source: false
  commercial: false
  callable_host: false
  label: Library · distributed through package registries, no callable service
  confidence: low
  source:
  - none
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source: []
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/sigopt.png
name: SigOpt
description: SigOpt was a machine learning experimentation and optimization platform whose API applied ensemble Bayesian and
  black-box optimization to tune model hyperparameters, run design-of-experiments, and track experiment metadata at scale.
  Developers integrated its REST API and first-party clients (Python, Java, R, scikit-learn, Spark, MATLAB) to drive automated
  hyperparameter search from their training loops. SigOpt was acquired by Intel in 2020 and its hosted API and platform were
  subsequently discontinued; sigopt.com now redirects to an Intel corporate redirector and the api./app./docs.sigopt.com hosts
  no longer resolve. The GitHub organization (github.com/sigopt) and the published client libraries remain public as historical,
  first-party artifacts, including an open-sourced server and optimization engine (sigopt-server, sigoptlite, libsigopt).
url: https://raw.githubusercontent.com/api-evangelist/sigopt/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- a16z
- dcvc
x-tier: stub
x-tier-reason: portfolio-lead
x-status: defunct
x-status-reason: Acquired by Intel (2020); hosted API/platform shut down. Only historical first-party packages and the public
  GitHub organization survive.
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-21'
tags:
- Company
- Machine Learning
- Optimization
- Hyperparameter Tuning
- Experimentation
- Bayesian Optimization
- MLOps
- Data Science
- Defunct
tags_raw:
- Company
- Machine Learning
- Optimization
- Hyperparameter Tuning
- Experimentation
- Bayesian Optimization
- MLOps
- Data Science
- Defunct
- Machine-Learning
apis: []
common:
- type: Website
  url: https://sigopt.com
- type: GitHubOrganization
  url: https://github.com/sigopt
- type: SourceCode
  url: https://github.com/sigopt
- type: Packages
  url: packages/sigopt-packages.yml
- type: SDKs
  url: packages/sigopt-packages.yml
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
x-enrichment:
  date: '2026-07-21'
  status: enriched
  artifacts_added: 1
  pass: local-v1

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