Emmi Ai

Emmi AI is an Austrian engineering-AI company building Large Engineering Models (LEMs) - pre-trained, physics-accurate neural networks that replace traditional CAE/CFD solvers to deliver real-time, GPU-accelerated simulation and design validation for manufacturing, aerospace, semiconductor, and energy engineering. Its flagship open-source Noether framework (the emmiai-noether PyTorch package) provides transformer building blocks, a model/dataset/recipe zoo, and a command-line toolchain for training, fine-tuning, and deploying industrial physics models, alongside vertical products such as NeuralWing (aircraft wing validation), NeuralMould (injection moulding), and NeuralDEM (particulate flows). Emmi AI was acquired by Mistral AI in May 2026 to build an industrial AI stack.

Emmi Ai is profiled on the APIs.io network. Tagged areas include Company, Engineering AI, Physics Simulation, Machine Learning, and Deep Learning.

Emmi Ai’s developer surface includes documentation, API reference, getting-started guide, engineering blog, support, CLI, changelog, and 11 more developer resources.

🌐 Visit website 📡 Source on GitHub

27.7/100 emerging ▬ flat Agent 0/100 human only Full breakdown ↓
scored 2026-07-27 · rubric v0.5

0 APIs

CompanyEngineering AIPhysics SimulationMachine LearningDeep LearningScientific ComputingCAECFDManufacturingOpen Source

Kin Score

Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5

Composite quality — 27.7/100 · emerging

Contract Quality 0.0 / 25

Developer Ergonomics 10.9 / 20

Commercial Clarity 7.4 / 20

Operational Transparency 2.7 / 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/emmi-ai: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

Get Started 2

Portal, sign-up, and the first successful call

DeveloperPortal

DeveloperPortal

GettingStarted

GettingStarted

Documentation 2

Reference material describing how the API behaves

Documentation

Documentation

APIReference

APIReference

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

Build 4

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

Packages

SDKs

CLI

Access & Security 3

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

TrustCenter

TrustCenter

Compliance

Compliance

Operate 2

Status, limits, changes, and where to get help

Support

Support

ChangeLog

ChangeLog

Commercial 2

Pricing, plans, and the legal terms of use

PrivacyPolicy

PrivacyPolicy

TermsOfService

TermsOfService

Company 2

The organization behind the API

Website

Website

Blog

Blog

Source (apis.yml)

aid: emmi-ai
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/emmi-ai.png
name: Emmi Ai
description: Emmi AI is an Austrian engineering-AI company building Large Engineering Models (LEMs) - pre-trained, physics-accurate
  neural networks that replace traditional CAE/CFD solvers to deliver real-time, GPU-accelerated simulation and design validation
  for manufacturing, aerospace, semiconductor, and energy engineering. Its flagship open-source Noether framework (the emmiai-noether
  PyTorch package) provides transformer building blocks, a model/dataset/recipe zoo, and a command-line toolchain for training,
  fine-tuning, and deploying industrial physics models, alongside vertical products such as NeuralWing (aircraft wing validation),
  NeuralMould (injection moulding), and NeuralDEM (particulate flows). Emmi AI was acquired by Mistral AI in May 2026 to build
  an industrial AI stack.
url: https://raw.githubusercontent.com/api-evangelist/emmi-ai/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- speedinvest
x-acquired-by: mistral-ai
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-19'
tags:
- Company
- Engineering AI
- Physics Simulation
- Machine Learning
- Deep Learning
- Scientific Computing
- CAE
- CFD
- Manufacturing
- Open Source
apis: []
common:
- type: DomainSecurity
  url: security/emmi-ai-domain-security.yml
- type: Website
  url: https://emmi.ai
- type: DeveloperPortal
  url: https://noether-docs.emmi.ai/
- type: Documentation
  url: https://noether-docs.emmi.ai/
- type: APIReference
  url: https://noether-docs.emmi.ai/
- type: GettingStarted
  url: https://noether-docs.emmi.ai/
- type: GitHubOrganization
  url: https://github.com/Emmi-AI
- type: Blog
  url: https://emmi.ai/news
- type: Support
  url: https://emmi.ai/contact-us
- type: PrivacyPolicy
  url: https://emmi.ai/privacy-policy
- type: TermsOfService
  url: https://emmi.ai/imprint
- type: Packages
  url: packages/emmi-ai-packages.yml
- type: SDKs
  url: packages/emmi-ai-packages.yml
- type: CLI
  url: cli/emmi-ai-cli.yml
- type: ChangeLog
  url: changelog/emmi-ai-changelog.yml
- type: LLMsTxt
  url: llms/emmi-ai-llms.txt
- type: TrustCenter
  url: security/emmi-ai-trust-center.yml
- type: Compliance
  url: https://emmi.ai/security-compliance
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