Latent Space

Latent Space is an artificial intelligence company building generative models for businesses and creatives, described by General Catalyst as creating "AI technology for predictive analytics and data-driven insights." The company raised a Series A from Greylock and General Catalyst and is listed in the General Catalyst portfolio under the Artificial Intelligence industry in North America. As of a July 2026 probe, Latent Space publishes no developer surface: the company domain latentspace.co returns an HTTP 302 redirect to its X/Twitter profile for every path probed, no docs/api/developer/app/status subdomains resolve in DNS, there are no /.well-known/ discovery documents, no llms.txt, and no public repositories under its GitHub organization. This profile therefore records verified company identity and domain posture only — no API, SDK, or documentation artifacts exist to harvest.

Latent Space is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Generative AI, Machine Learning, and Predictive Analytics.

🌐 Visit website 📡 Profile data on GitHub

4.4/100 minimal ▬ flat Agent 0/100 human only Front door AI 3/6 light Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

0 APIs

Company Artificial Intelligence Generative AI Machine Learning Predictive Analytics North America

Kin Score

Kin Score How this is scored →
scored 2026-11-06 · rubric v0.27.0

Composite quality — 4.4/100 · minimal

Contract Quality 0.0 / 21

Developer Ergonomics 0.0 / 17

Access Clarity 0.0 / 17

Operational Transparency 0.6 / 11

Contract Governance 0.0 / 10

Discoverability 4.7 / 9

Regulatory Posture 0.8 / 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

Pagination 5 / 5

Distinct Operations 3 / 3

MCP Tool Quality 6 / 6

Regulatory Posture applies to this provider. Its tags matched the AI & Biometrics 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/.

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Agent readiness — checks not met, largest first (exact, from this profile):

Machine-Readable Contract +18 pts — api_specs includes an OpenAPI document
MCP Server +12 pts — deployment.mode + probe verdict on the mcp/ manifest, not the pointer; an unprobed slug falls back to authorship
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author
Machine-Readable Auth +10 pts — a served openid-configuration/oauth-authorization-server carrying `issuer` (served), else the securitySchemes class in the provider OpenAPIs — bound (mutualTLS, DPoP, Signature) > negotiable (oauth2 authorizationCode/clientCredentials, openIdConnect) > bearer (http bearer, apiKey)
Idempotency +9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented)
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes

13 more unmet checks in the Agent Readiness table above.

Kin Score — facets with the most composite points still available (weight × headroom):

Contract Quality scores 0.0 — up to +25.0 composite points
Developer Ergonomics scores 0.0 — up to +20.0 composite points
Access Clarity scores 0.0 — up to +20.0 composite points

Each check links to what satisfies it. Publish the artifact, or tell us where it already lives, and the score moves on the next scoring run.

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 the provider profile at artifacts.apis.io/latent-space/apis.yml: open an issue on github.com/api-evangelist/latent-space to ask a question or point us at an artifact you publish. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Markets this provider is in provisional

The Kin Score Market layer reads a provider inside its market: its position, and how deep its integrations go. Depth is only comparable within a position. Provisional and unweighted: not part of the Kin Score or agent readiness.

Market	Position	Depth	Registered MCP server	Declares compatibility
VC Portfolios (a16z, Battery Ventures, Sequoia Capital, Index Ventures participation)	undeclared	-	-	-

Registered MCP server and declares compatibility are report only — not weighted. Undeclared means we found nothing we can read, so there is no number: we never infer integrations.

Security Posture 1

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

Latent Space Domain Security

TLSv1.3 · HSTS · DNSSEC

SECURITY

Resources

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

WellKnown

WellKnown

LLMsTxt

LLMsTxt

Build 1

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Company 4

The organization behind the API

Website

Website

Twitter

Twitter

LinkedIn

Investors

Investors

Source (apis.yml)

aid: latent-space
name: Latent Space
description: 'Latent Space is an artificial intelligence company building generative models for businesses and creatives,
  described by General Catalyst as creating "AI technology for predictive analytics and data-driven insights." The company
  raised a Series A from Greylock and General Catalyst and is listed in the General Catalyst portfolio under the Artificial
  Intelligence industry in North America. As of a July 2026 probe, Latent Space publishes no developer surface: the company
  domain latentspace.co returns an HTTP 302 redirect to its X/Twitter profile for every path probed, no docs/api/developer/app/status
  subdomains resolve in DNS, there are no /.well-known/ discovery documents, no llms.txt, and no public repositories under
  its GitHub organization. This profile therefore records verified company identity and domain posture only — no API, SDK,
  or documentation artifacts exist to harvest.'
url: https://raw.githubusercontent.com/api-evangelist/latent-space/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:
  - security
  generated: '2026-11-06'
  method: derived
image: https://pbs.twimg.com/profile_images/1168960746237112320/hUVM_19-_400x400.jpg
x-type: company
x-source: vc-portfolio
x-backed-by:
- general-catalyst
- greylock
x-tier: stub
x-tier-reason: no-public-developer-surface
x-enrichment:
  last_run: '2026-07-19'
  outcome: identity-verified-no-api-surface
  evidence:
  - https://www.generalcatalyst.com/companies/latent-space
  - https://x.com/latentspaceai
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-19'
tags:
- Company
- Artificial Intelligence
- Generative AI
- Machine Learning
- Predictive Analytics
- North America
tags_raw:
- Company
- Artificial Intelligence
- Generative AI
- Machine Learning
- Predictive Analytics
- Venture Backed
- North America
- Machine-Learning
apis: []
common:
- url: https://www.latentspace.co/
  type: Website
  name: Latent Space website (302 redirects to X/Twitter as of 2026-07-19)
- url: https://x.com/latentspaceai
  type: Twitter
  name: Latent Space on X
- url: https://www.linkedin.com/company/latentspaceai/
  type: LinkedIn
  name: Latent Space on LinkedIn
- url: https://github.com/latentspaceai
  type: GitHubOrganization
  name: Latent Space GitHub organization (no public repositories)
- url: https://www.generalcatalyst.com/companies/latent-space
  type: Investors
  name: General Catalyst portfolio profile
- url: security/latent-space-domain-security.yml
  type: DomainSecurity
  name: Domain and TLS security posture
- url: well-known/latent-space-well-known.yml
  type: WellKnown
  name: Well-known discovery probe results
- url: llms/latent-space-llms.txt
  type: LLMsTxt
  name: llms.txt for Latent Space
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io

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