Envariant

Envariant is building the control layer for foundation models — an AI interpretability SDK that lets teams inspect, steer, and control model behavior. The SDK exposes a compact set of primitives: detect and causally trace behaviors like hallucinations or invariant violations, reason inductively and steer outputs programmatically, extract human-readable domain principles, and synthesize targeted edge cases — moving verification upstream, directly into the model's latent space, with no bespoke engineering required. Envariant is a Y Combinator (Winter 2026) company based in San Francisco. The SDK is in pre-release beta, so no public API, OpenAPI, or developer documentation is available yet; this profile captures the company identity ahead of a public developer surface.

Envariant is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Interpretability, Foundation Models, and Machine Learning.

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

🌐 Visit website 📡 Profile data on GitHub

3.4/100 minimal ▬ flat Agent 0/100 human only Front door AI 4/6 moderate Full breakdown ↓
scored 2026-10-17 · rubric v0.24.0

0 APIs

Company Artificial Intelligence Interpretability Foundation Models Machine Learning AI SafetyModel SteeringLLM Hallucination Detection Developer Tools SDK

Kin Score

Kin Score How this is scored →
scored 2026-10-17 · rubric v0.24.0

Composite quality — 3.4/100 · minimal

Contract Quality 0.0 / 21

Developer Ergonomics 0.4 / 17

Access Clarity 0.0 / 17

Operational Transparency 0.0 / 11

Contract Governance 0.0 / 10

Discoverability 4.1 / 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

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/.

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 github.com/api-evangelist/envariant: open an issue to ask a question, or submit a pull request to add artifacts. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Security Posture 1

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

Envariant Domain Security

TLSv1.3

SECURITY

Resources

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Company 2

The organization behind the API

Blog

Blog

Website

Website

Source (apis.yml)

aid: envariant
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://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/envariant.png
name: Envariant
description: 'Envariant is building the control layer for foundation models — an AI interpretability SDK that lets teams inspect,
  steer, and control model behavior. The SDK exposes a compact set of primitives: detect and causally trace behaviors like
  hallucinations or invariant violations, reason inductively and steer outputs programmatically, extract human-readable domain
  principles, and synthesize targeted edge cases — moving verification upstream, directly into the model''s latent space,
  with no bespoke engineering required. Envariant is a Y Combinator (Winter 2026) company based in San Francisco. The SDK
  is in pre-release beta, so no public API, OpenAPI, or developer documentation is available yet; this profile captures the
  company identity ahead of a public developer surface.'
url: https://raw.githubusercontent.com/api-evangelist/envariant/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- y-combinator
x-tier: stub
x-tier-reason: portfolio-lead
x-batch: W2026
x-location: San Francisco, CA, USA
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-10-06'
tags:
- Company
- Artificial Intelligence
- Interpretability
- Foundation Models
- Machine Learning
- AI Safety
- Model Steering
- LLM
- Hallucination Detection
- Developer Tools
- SDK
tags_raw:
- Company
- Artificial Intelligence
- Interpretability
- Foundation Models
- Machine Learning
- AI Safety
- Model Steering
- LLM
- Hallucination Detection
- Developer Tools
- SDK
- Machine-Learning
common:
- url: https://envariant.ai/blog/
  type: Blog
- type: DomainSecurity
  url: security/envariant-domain-security.yml
- type: Website
  url: https://envariant.ai/
apis: []
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

Work with this as data

Every provider here is available over the APIs.io API and to AI agents over MCP.

MCP server

One button, every client — Claude, Cursor, VS Code and the rest.

https://apis.io/mcp

Tools for providers

9 MCP tools reach this

find_providersBrowse and filter every provider in the catalog.
get_provider_artifactsEvery artifact this provider publishes, grouped by type.
get_provider_operationsEvery operation across all of their OpenAPIs — one call instead of parsing every spec.
get_provider_toolsEvery MCP tool they ship, with the operation each wraps.
get_provider_evidenceHow each part of their score was established. Free — the basis for a claim should not sit behind it.
get_provider_ratingPRO — composite, band, trend and facet scores.
apis_io_searchSTART HERE — APIs, providers and tags for one query, each with its total.
resolveTurn a domain, URL or GitHub org into the provider it belongs to.
find_cohortsEvery scored population of providers in the catalog.

All 92 tools →

Call it yourself

curl for this page

This provider

curl "https://apis.io/api/v1/providers/envariant"

All providers

curl "https://apis.io/api/v1/providers?limit=25"

Every operation they expose

curl "https://apis.io/api/v1/providers/envariant/operations?limit=25"

How their score was established

curl "https://apis.io/api/v1/providers/envariant/evidence"

Discovery needs no key. Ratings and market analysis are Pro.

Get an API key

Free tier, no form to fill in. Signing in shares your email address with us — we store it to create your key and to recognise you if you sign in with another provider. See our Privacy Policy and Terms.

GitHub Google LinkedIn

A second provider on the same verified email joins the account you already have.