Autoscience

Autoscience (Autoscience Institute) builds AI systems that train state-of-the-art models for frontier and applied AI labs. The company automates AI research itself, developing agents and infrastructure that design, run, and evaluate machine-learning experiments to accelerate model development and automated scientific discovery. Autoscience is an early-stage AI research company backed by General Catalyst and is hiring engineers, researchers, and designers. It currently publishes a marketing site, a research blog, and a careers page; no public API, developer portal, SDKs, or machine-readable API specifications have been located at this time.

Autoscience is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Machine-Learning, AI Research, and Automated Research.

Autoscience’s developer surface includes engineering blog and 2 more developer resources.

🌐 Visit website 📡 Source on GitHub

5.5/100 minimal ▬ flat Agent 0/100 human only Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0

0 APIs

Company Artificial Intelligence Machine-Learning AI ResearchAutomated ResearchModel Training Frontier Models

Kin Score

Kin Score How this is scored →
scored 2026-09-08 · rubric v0.20.0

Composite quality — 5.5/100 · minimal

Contract Quality 0.0 / 25

Developer Ergonomics 0.5 / 20

Access Clarity 0.0 / 20

Operational Transparency 0.0 / 13

Contract Governance 0.0 / 12

Discoverability 5.0 / 10

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

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.

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Security Posture 1

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

Autoscience Domain Security

TLSv1.3 · DNSSEC · DMARC

SECURITY

Resources

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Company 2

The organization behind the API

Website

Website

Blog

Blog

Source (apis.yml)

aid: autoscience
name: Autoscience
description: Autoscience (Autoscience Institute) builds AI systems that train state-of-the-art models for frontier and applied
  AI labs. The company automates AI research itself, developing agents and infrastructure that design, run, and evaluate machine-learning
  experiments to accelerate model development and automated scientific discovery. Autoscience is an early-stage AI research
  company backed by General Catalyst and is hiring engineers, researchers, and designers. It currently publishes a marketing
  site, a research blog, and a careers page; no public API, developer portal, SDKs, or machine-readable API specifications
  have been located at this time.
url: https://raw.githubusercontent.com/api-evangelist/autoscience/refs/heads/main/apis.yml
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://www.autoscience.ai/auto-home/assets/logo-autoscience.png
x-type: company
x-source: vc-portfolio
x-backed-by:
- general-catalyst
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-18'
tags:
- Company
- Artificial Intelligence
- Machine-Learning
- AI Research
- Automated Research
- Model Training
- Frontier Models
tags_raw:
- Company
- Ai
- Machine Learning
- AI Research
- Automated Research
- Model Training
- Frontier Models
apis: []
common:
- type: DomainSecurity
  url: security/autoscience-domain-security.yml
- type: Website
  url: https://www.autoscience.ai/
- type: Blog
  url: https://www.autoscience.ai/blog
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

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