Unconventional AI

Unconventional AI (unconv.ai) is rethinking the foundations of the computer to optimize energy efficiency for AI, working to bring biology-scale efficiency to artificial intelligence through analog, dynamical-system hardware co-evolved with neural software. Founded by experts in AI systems, analog circuits, computing theory, and neuroscience, and backed by Felicis, the company publishes research including the Un-0 image-generation model built on coupled Kuramoto oscillators and an instruction set architecture for dynamical-system hardware, but does not yet publish a public API, developer portal, or SDKs.

Unconventional AI is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, AI Hardware, Analog Computing, and Energy Efficiency.

Unconventional AI’s developer surface includes engineering blog and 4 more developer resources.

🌐 Visit website 📡 Source on GitHub

7.9/100 minimal ▬ flat Agent 0/100 human only Full breakdown ↓
scored 2026-07-27 · rubric v0.5

0 APIs

CompanyArtificial IntelligenceAI HardwareAnalog ComputingEnergy EfficiencyMachine LearningSemiconductors

Kin Score

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

Composite quality — 7.9/100 · minimal

Contract Quality 0.0 / 25

Developer Ergonomics 0.4 / 20

Commercial Clarity 0.0 / 20

Operational Transparency 0.7 / 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/unconv: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

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

Company 2

The organization behind the API

Website

Website

Blog

Blog

Source (apis.yml)

aid: unconv
name: Unconventional AI
description: Unconventional AI (unconv.ai) is rethinking the foundations of the computer to optimize energy efficiency for
  AI, working to bring biology-scale efficiency to artificial intelligence through analog, dynamical-system hardware co-evolved
  with neural software. Founded by experts in AI systems, analog circuits, computing theory, and neuroscience, and backed
  by Felicis, the company publishes research including the Un-0 image-generation model built on coupled Kuramoto oscillators
  and an instruction set architecture for dynamical-system hardware, but does not yet publish a public API, developer portal,
  or SDKs.
url: https://raw.githubusercontent.com/api-evangelist/unconv/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://github.com/unconv-ai.png
x-type: company
x-source: vc-portfolio
x-backed-by:
- felicis
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.20'
x-enrichment:
  date: '2026-07-21'
  status: minimal
  artifacts_added: 3
  pass: local-v1
created: '2026-07-17'
modified: '2026-07-21'
tags:
- Company
- Artificial Intelligence
- AI Hardware
- Analog Computing
- Energy Efficiency
- Machine Learning
- Semiconductors
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://unconv.ai
- type: Blog
  url: https://unconv.ai/blog/
- type: GitHubOrganization
  url: https://github.com/unconv-ai
- type: LLMsTxt
  url: llms/unconv-llms.txt
- type: DomainSecurity
  url: security/unconv-domain-security.yml