Autoscience website screenshot

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, Ai, Machine Learning, AI Research, and Automated Research.

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

🌐 Visit website 📡 Source on GitHub
7.2/100 minimal ▬ flat Agent 0/100 human only Full breakdown ↓
scored 2026-07-27 · rubric v0.5
0 APIs
CompanyAiMachine LearningAI ResearchAutomated ResearchModel TrainingFrontier Models

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 7.2/100 · minimal
Contract Quality 0.0 / 25
Developer Ergonomics 0.4 / 20
Commercial Clarity 0.0 / 20
Operational Transparency 0.0 / 13
Governance 0.0 / 12
Discoverability 6.8 / 10
Agent readiness — 0/100 · human only
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 15
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
Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. This rating is computed from github.com/api-evangelist/autoscience: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

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)

apis.yml Raw ↑ 
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
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: '0.20'
created: '2026-07-17'
modified: '2026-07-18'
tags:
- 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