Belvedir

Belvedir is an autonomous private AI platform built by Fractal Machine Research, Inc. (a Y Combinator Summer 2026 company). It lets individuals and teams train custom AI models and memory systems, host them privately on single-tenant infrastructure, and continually improve them through use: it collects agent calls and production traces, converts those traces into training data, and fine-tunes models with reinforcement learning in a continuous loop before redeploying on private infrastructure. The stated aim is to let everyday individuals own their own artificial intelligence rather than rent it from a shared provider. The product is in closed alpha and access is currently granted by request; there is no public API or developer documentation yet, so this profile captures the company's public identity and will be enriched as a developer surface appears.

Belvedir is profiled on the APIs.io network. Tagged areas include Company, Artificial Intelligence, Machine-Learning, Reinforcement Learning, and Private AI.

Belvedir’s developer surface includes engineering blog, changelog, and 7 more developer resources.

🌐 Visit website 📡 Source on GitHub

11.8/100 emerging ▬ flat Agent 0/100 human only saas Full breakdown ↓
scored 2026-09-08 · rubric v0.20.0

0 APIs

Company Artificial Intelligence Machine-Learning Reinforcement Learning Private AI Fine-Tuning LLM Agents Model Hosting

Kin Score

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

Composite quality — 11.8/100 · emerging

Contract Quality 0.0 / 25

Developer Ergonomics 0.5 / 20

Access Clarity 4.2 / 20

Operational Transparency 2.1 / 13

Contract Governance 0.0 / 12

Discoverability 5.0 / 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.

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/belvedir: 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.

Belvedir Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Operate 2

Status, limits, changes, and where to get help

ChangeLog

ChangeLog

ChangeLog

ChangeLog

Commercial 2

Pricing, plans, and the legal terms of use

TermsOfService

TermsOfService

PrivacyPolicy

PrivacyPolicy

Company 4

The organization behind the API

Website

Website

Blog

Blog

LinkedIn

Twitter

Twitter

Source (apis.yml)

aid: belvedir
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
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/belvedir.png
name: Belvedir
description: 'Belvedir is an autonomous private AI platform built by Fractal Machine Research, Inc. (a Y Combinator Summer
  2026 company). It lets individuals and teams train custom AI models and memory systems, host them privately on single-tenant
  infrastructure, and continually improve them through use: it collects agent calls and production traces, converts those
  traces into training data, and fine-tunes models with reinforcement learning in a continuous loop before redeploying on
  private infrastructure. The stated aim is to let everyday individuals own their own artificial intelligence rather than
  rent it from a shared provider. The product is in closed alpha and access is currently granted by request; there is no public
  API or developer documentation yet, so this profile captures the company''s public identity and will be enriched as a developer
  surface appears.'
url: https://raw.githubusercontent.com/api-evangelist/belvedir/refs/heads/main/apis.yml
x-api-posture: no-product-api
x-api-posture-basis: observed
x-api-posture-note: The product is in closed alpha and access is currently granted by request; there is no public API or developer
  documentation yet, so this profile captures the company's public identity and will be enr
x-type: company
x-source: vc-portfolio
x-backed-by:
- y-combinator
x-tier: stub
x-tier-reason: portfolio-lead
x-legal-name: Fractal Machine Research, Inc.
x-yc-batch: Summer 2026
x-headquarters: San Francisco, CA
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-18'
tags:
- Company
- Artificial Intelligence
- Machine-Learning
- Reinforcement Learning
- Private AI
- Fine-Tuning
- LLM
- Agents
- Model Hosting
tags_raw:
- Company
- Artificial Intelligence
- Machine Learning
- Reinforcement Learning
- Private AI
- Fine-Tuning
- LLM
- Agents
- Model Hosting
apis: []
common:
- url: https://belvedir.ai/
  type: Website
- url: https://belvedir.ai/blog
  type: Blog
- url: https://belvedir.ai/releases
  type: ChangeLog
- url: changelog/belvedir-changelog.yml
  type: ChangeLog
- url: https://belvedir.ai/terms
  type: TermsOfService
- url: https://belvedir.ai/privacy
  type: PrivacyPolicy
- url: https://www.linkedin.com/company/fractal-machine-research/
  type: LinkedIn
- url: https://x.com/fractalml
  type: Twitter
- url: security/belvedir-domain-security.yml
  type: DomainSecurity
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

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