Skipjaq

Skipjaq, Inc. was a machine-learning performance-optimisation startup that marketed itself as "Performance Optimisation as a Service" and was backed by Accel. Its proprietary automated workload-optimisation software ran repeated optimization tests against a customer's application (hosted in the cloud on AWS EC2 instances behind Elastic Load Balancers) and used machine learning to tune configuration for better application performance, throughput, and latency without manual, expert tuning. The product was delivered as a cloud SaaS and was offered under a beta test agreement. The company is now defunct: the skipjaq.com domain no longer resolves on any common TLD (.com/.io/.ai/.co.uk all return no A/NS records as of 2026-07-21), the last archived snapshot of the site dates to May 2025, and there is no public developer portal, OpenAPI/Swagger specification, first-party SDK, or live API surface. This profile was surfaced as an Accel portfolio lead.

Skipjaq is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Machine Learning, Performance Optimization, and Performance Testing.

0.0/100 minimal Agent 0/100 human only Full breakdown ↓
scored 2026-09-25 · rubric v0.23.0
0 APIs
CompanyArtificial IntelligenceMachine LearningPerformance OptimizationPerformance TestingLoad TestingCloudDevOpsSoftware-as-a-ServiceDefunct

Kin Score

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

Company 1

The organization behind the API

Source (apis.yml)

apis.yml Raw ↑
aid: skipjaq
deliveryModel:
  model: unknown
  open_source: false
  commercial: false
  callable_host: false
  label: Delivery model not determined — needs a product licence on record
  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/skipjaq.png
name: Skipjaq
description: 'Skipjaq, Inc. was a machine-learning performance-optimisation startup that marketed itself as "Performance Optimisation
  as a Service" and was backed by Accel. Its proprietary automated workload-optimisation software ran repeated optimization
  tests against a customer''s application (hosted in the cloud on AWS EC2 instances behind Elastic Load Balancers) and used
  machine learning to tune configuration for better application performance, throughput, and latency without manual, expert
  tuning. The product was delivered as a cloud SaaS and was offered under a beta test agreement. The company is now defunct:
  the skipjaq.com domain no longer resolves on any common TLD (.com/.io/.ai/.co.uk all return no A/NS records as of 2026-07-21),
  the last archived snapshot of the site dates to May 2025, and there is no public developer portal, OpenAPI/Swagger specification,
  first-party SDK, or live API surface. This profile was surfaced as an Accel portfolio lead.'
url: https://raw.githubusercontent.com/api-evangelist/skipjaq/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- accel
x-tier: stub
x-tier-reason: portfolio-lead
x-status: defunct
x-status-evidence:
- 'DNS: no A or NS records for skipjaq.com, skipjaq.io, skipjaq.ai, or skipjaq.co.uk (probed 2026-07-21)'
- 'Wayback: last archived snapshot 2025-05-16; 2018 snapshots describe "Performance Optimisation as a Service" by SKIPJAQ,
  Inc.'
- 'GitHub: no official skipjaq organization (404); only third-party skipjaq-artifacts test-run repos from 2017-2018'
- No public OpenAPI, SDK, developer portal, or live API surface found
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-21'
tags:
- Company
- Artificial Intelligence
- Machine Learning
- Performance Optimization
- Performance Testing
- Load Testing
- Cloud
- DevOps
- Software-as-a-Service
- Defunct
tags_raw:
- Company
- Ai
- Machine Learning
- Performance Optimization
- Performance Testing
- Load Testing
- Cloud
- DevOps
- SaaS
- Defunct
- Machine-Learning
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://skipjaq.com
x-enrichment:
  date: '2026-07-21'
  status: minimal
  artifacts_added: 0
  pass: local-v1

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