Guide Labs

Guide Labs is a product-focused AI research company building a new class of inherently interpretable AI systems and foundation models that humans and domain experts can reliably understand, steer, and debug. Its flagship platform, Clarity, is presented as the first inherently interpretable AI platform and surfaces the internal concepts driving a model's decisions, while its Steerling-8B is presented as the first inherently interpretable large language model. The team has published more than two dozen interpretability papers at top machine-learning venues and ships research artifacts such as PRISM training-data prototypes, the FineWeb Concept Atlas, and Atlas for orienting LLM pre-training data. Access to Clarity is available through platform.guidelabs.ai. The company is backed by Initialized Capital.

Guide Labs is profiled on the APIs.io network. Tagged areas include Company, Enterprise Saas, Artificial Intelligence, Interpretability, and Machine-Learning.

Guide Labs’ developer surface includes engineering blog and 7 more developer resources.

🌐 Visit website 📡 Source on GitHub

10.0/100 minimal ▬ flat Agent 0/100 human only saas Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0

0 APIs

Company Enterprise Saas Artificial Intelligence Interpretability Machine-Learning Foundation Models Large Language Models AI Safety Research

Kin Score

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

Composite quality — 10.0/100 · minimal

Contract Quality 0.0 / 25

Developer Ergonomics 0.5 / 20

Access Clarity 3.4 / 20

Operational Transparency 0.3 / 13

Contract Governance 0.0 / 12

Discoverability 5.7 / 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.

Guide Labs Domain Security

TLSv1.3 · DNSSEC · DMARC

SECURITY

Resources

Get Started 1

Portal, sign-up, and the first successful call

Login

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

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

Commercial 1

Pricing, plans, and the legal terms of use

PrivacyPolicy

PrivacyPolicy

Company 3

The organization behind the API

Website

Website

Blog

Blog

About

About

Source (apis.yml)

aid: guide-labs
name: Guide Labs
description: Guide Labs is a product-focused AI research company building a new class of inherently interpretable AI systems
  and foundation models that humans and domain experts can reliably understand, steer, and debug. Its flagship platform, Clarity,
  is presented as the first inherently interpretable AI platform and surfaces the internal concepts driving a model's decisions,
  while its Steerling-8B is presented as the first inherently interpretable large language model. The team has published more
  than two dozen interpretability papers at top machine-learning venues and ships research artifacts such as PRISM training-data
  prototypes, the FineWeb Concept Atlas, and Atlas for orienting LLM pre-training data. Access to Clarity is available through
  platform.guidelabs.ai. The company is backed by Initialized Capital.
url: https://raw.githubusercontent.com/api-evangelist/guide-labs/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- initialized-capital
x-tier: stub
x-tier-reason: portfolio-lead
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: false
  label: Hosted service · you call their endpoint
  confidence: medium
  source:
  - pricing
  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
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-19'
image: https://www.guidelabs.ai/logo/guidelabs-social-media-thumbnail.png
tags:
- Company
- Enterprise Saas
- Artificial Intelligence
- Interpretability
- Machine-Learning
- Foundation Models
- Large Language Models
- AI Safety
- Research
tags_raw:
- Company
- Enterprise Saas
- Artificial Intelligence
- Interpretability
- Machine Learning
- Foundation Models
- Large Language Models
- AI Safety
- Research
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: DomainSecurity
  url: security/guide-labs-domain-security.yml
- type: LLMsTxt
  url: llms/guide-labs-llms.txt
- type: Website
  url: https://www.guidelabs.ai/
- type: Login
  url: https://platform.guidelabs.ai/
- type: Blog
  url: https://www.guidelabs.ai/blog/
- type: About
  url: https://www.guidelabs.ai/about-us/
- type: PrivacyPolicy
  url: https://www.guidelabs.ai/privacy-notice/
- type: GitHubOrganization
  url: https://github.com/guidelabs
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

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