Aizon

Aizon is a B2B SaaS manufacturing-intelligence platform for GxP pharmaceutical manufacturers and CDMOs. It turns process data into AI-driven recommendations to increase yield, reduce deviations, and prevent batch loss without replacing existing MES, LIMS, ERP, or historian systems. The platform spans four connected products: Aizon Execute (intelligent electronic batch records), Aizon Unify (a GxP manufacturing data platform / lakehouse), Aizon Predict (operationalized ML for yield optimization, CPV, and predictive quality), and Aizon Agentic Studio (a natural-language application and dashboard builder). Aizon runs single-tenant on AWS with ALCOA++ data integrity, 21 CFR Part 11 e-signatures, and a GxP model lifecycle, and exposes a RESTful API to customers. Offices in San Francisco, USA and Barcelona, Spain.

Aizon is profiled on the APIs.io network. Tagged areas include Company, Pharmaceutical Manufacturing, Life Sciences, Artificial Intelligence, and Machine Learning.

Aizon’s developer surface includes engineering blog, support, signup flow, and 9 more developer resources.

🌐 Visit website 📡 Source on GitHub

20.1/100 emerging ▬ flat Agent 0/100 human only Full breakdown ↓
scored 2026-07-27 · rubric v0.5

0 APIs

CompanyPharmaceutical ManufacturingLife SciencesArtificial IntelligenceMachine LearningManufacturing IntelligenceGxPData PlatformQuality

Kin Score

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

Composite quality — 20.1/100 · emerging

Contract Quality 0.0 / 25

Developer Ergonomics 1.3 / 20

Commercial Clarity 7.9 / 20

Operational Transparency 0.0 / 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/aizon: 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 1

Portal, sign-up, and the first successful call

SignUp

SignUp

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

Design & Contract 1

Pagination, idempotency, versioning, errors, and events

Conformance

Conformance

Access & Security 4

Authentication, authorization, and security posture

TrustCenter

Compliance

TrustCenter

DomainSecurity

Operate 1

Status, limits, changes, and where to get help

Support

Support

Commercial 1

Pricing, plans, and the legal terms of use

PrivacyPolicy

PrivacyPolicy

Company 3

The organization behind the API

Website

Website

Blog

Blog

LinkedIn

Source (apis.yml)

aid: aizon
name: Aizon
description: 'Aizon is a B2B SaaS manufacturing-intelligence platform for GxP pharmaceutical manufacturers and CDMOs. It turns
  process data into AI-driven recommendations to increase yield, reduce deviations, and prevent batch loss without replacing
  existing MES, LIMS, ERP, or historian systems. The platform spans four connected products: Aizon Execute (intelligent electronic
  batch records), Aizon Unify (a GxP manufacturing data platform / lakehouse), Aizon Predict (operationalized ML for yield
  optimization, CPV, and predictive quality), and Aizon Agentic Studio (a natural-language application and dashboard builder).
  Aizon runs single-tenant on AWS with ALCOA++ data integrity, 21 CFR Part 11 e-signatures, and a GxP model lifecycle, and
  exposes a RESTful API to customers. Offices in San Francisco, USA and Barcelona, Spain.'
url: https://raw.githubusercontent.com/api-evangelist/aizon/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- uncork-capital
x-tier: stub
x-tier-reason: portfolio-lead
accessModel:
  pricing: unknown
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Unknown
  confidence: low
  source: []
  generated: '2026-07-22'
  method: derived
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-17'
image: https://cdn.prod.website-files.com/66059e0331df02f19a296791/69b1436247ee4599e097fe41_AAAs%20logo%20-%20app%20image%20(4)%201.png
tags:
- Company
- Pharmaceutical Manufacturing
- Life Sciences
- Artificial Intelligence
- Machine Learning
- Manufacturing Intelligence
- GxP
- Data Platform
- Quality
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://www.aizon.ai
- type: Blog
  url: https://www.aizon.ai/blog
- type: Support
  url: https://www.aizon.ai/contact
- type: SignUp
  url: https://www.aizon.ai/book-demo
- type: PrivacyPolicy
  url: https://www.aizon.ai/privacy-policy
- type: TrustCenter
  url: https://www.aizon.ai/trust-center
- type: Compliance
  url: https://www.aizon.ai/trust-center
- type: LinkedIn
  url: https://www.linkedin.com/company/aizon/
- type: LLMsTxt
  url: llms/aizon-llms.txt
- type: TrustCenter
  url: security/aizon-trust-center.yml
- type: Conformance
  url: conformance/aizon-conformance.yml
- type: DomainSecurity
  url: security/aizon-domain-security.yml
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence