Generalist AI website screenshot

Generalist AI

Generalist AI is a frontier AI research and product company founded in 2024 that is building general intelligence for the physical world. Rather than manufacturing robots, Generalist builds the embodied foundation models — the "brain" — that run across many robot types and hardware configurations, with an emphasis on dexterity and autonomy. Its founding team of researchers, roboticists, and operators comes from Google DeepMind, Boston Dynamics, and OpenAI, with prior work on PaLM-E, RT-2, Gemini Robotics, Atlas, Spot, and the scaling of large language models. The company's GEN-1 model (April 2026) is described as the first general-purpose model to reach mastery of simple physical tasks, running with full autonomy. Generalist operates from the Bay Area (San Mateo / San Francisco) and Boston, and has raised more than $500M — including a $400M round at a roughly $2B valuation backed by Nvidia, Bezos Expeditions, Radical Ventures, 8VC, Union Square Ventures, Norwest Venture Partners, Hanabi Capital, and boldstart ventures. Generalist AI currently publishes no public API or developer program; this profile captures its company identity and web presence for the API Evangelist network.

Generalist AI is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Robotics, Foundation Models, and Physical AI.

Generalist AI’s developer surface includes engineering blog, YouTube channel, and 7 more developer resources.

7.2/100 minimal ▬ flat Agent 0/100 human only Full breakdown ↓
scored 2026-07-27 · rubric v0.5
0 APIs
CompanyArtificial IntelligenceRoboticsFoundation ModelsPhysical AIEmbodied AIMachine LearningResearch

Kin Score

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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/generalistai: 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.

Generalistai Domain Security

TLSv1.3 · HSTS · DNSSEC · DMARC

SECURITY

Resources

Access & Security 1

Authentication, authorization, and security posture

Learn 1

Tutorials, courses, talks, and written guidance

Operate 1

Status, limits, changes, and where to get help

Company 5

The organization behind the API

Other 1

Properties that don't map to a standard resource type

Source (apis.yml)

apis.yml Raw ↑
aid: generalistai
name: Generalist AI
description: Generalist AI is a frontier AI research and product company founded in 2024 that is building general intelligence
  for the physical world. Rather than manufacturing robots, Generalist builds the embodied foundation models — the "brain"
  — that run across many robot types and hardware configurations, with an emphasis on dexterity and autonomy. Its founding
  team of researchers, roboticists, and operators comes from Google DeepMind, Boston Dynamics, and OpenAI, with prior work
  on PaLM-E, RT-2, Gemini Robotics, Atlas, Spot, and the scaling of large language models. The company's GEN-1 model (April
  2026) is described as the first general-purpose model to reach mastery of simple physical tasks, running with full autonomy.
  Generalist operates from the Bay Area (San Mateo / San Francisco) and Boston, and has raised more than $500M — including
  a $400M round at a roughly $2B valuation backed by Nvidia, Bezos Expeditions, Radical Ventures, 8VC, Union Square Ventures,
  Norwest Venture Partners, Hanabi Capital, and boldstart ventures. Generalist AI currently publishes no public API or developer
  program; this profile captures its company identity and web presence for the API Evangelist network.
url: https://raw.githubusercontent.com/api-evangelist/generalistai/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://generalistai.com/assets/images/generalist-og-image.jpg
x-type: company
x-source: vc-portfolio
x-backed-by:
- norwest-venture-partners
x-tier: profile
x-tier-reason: portfolio-lead-enriched
x-founded: '2024'
x-headquarters: San Mateo, California; Boston, Massachusetts
x-founders:
- Pete Florence
- Andy Zeng
- Andrew Barry
x-investors:
- Nvidia
- Bezos Expeditions
- Radical Ventures
- 8VC
- Union Square Ventures
- Norwest Venture Partners
- Hanabi Capital
- boldstart ventures
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-19'
tags:
- Company
- Artificial Intelligence
- Robotics
- Foundation Models
- Physical AI
- Embodied AI
- Machine Learning
- Research
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://generalistai.com
- type: Blog
  url: https://generalistai.com/blog
- type: About
  url: https://generalistai.com/about
- type: Careers
  url: https://generalistai.com/careers
- type: Contact
  url: https://generalistai.com/contact
- type: LinkedIn
  url: https://www.linkedin.com/company/generalistai
- type: X
  url: https://x.com/GeneralistAI
- type: YouTube
  url: https://www.youtube.com/@GeneralistAI
- type: DomainSecurity
  url: security/generalistai-domain-security.yml
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence