Synthefy

Synthefy builds foundation models for structured data, replacing task-specific machine learning (XGBoost, LightGBM, ARIMA, Prophet) with a single API call. Its Nori tabular model performs in-context regression and classification on any table with no training, and its time-series Forecasting API (Migas-1.0) delivers multivariate probabilistic forecasts with exogenous context. The platform is delivered as a hosted REST API, Python SDKs, Docker containers, AWS SageMaker, and Snowflake, serving banking, retail, insurance, healthcare, infrastructure, and marketing use cases with SOC 2 Type II, HIPAA, GDPR, and zero-data-retention compliance.

Synthefy publishes 2 APIs on the APIs.io network. Tagged areas include Company, Foundation Models, Machine Learning, Forecasting, and Time Series.

Synthefy’s developer surface includes documentation, API reference, getting-started guide, engineering blog, support, signup flow, authentication, and 16 more developer resources.

31.8/100 thin ▬ flat Agent 28/100 agent aware Full breakdown ↓
scored 2026-07-27 · rubric v0.5
AccessSelf serve
2 APIs 1 MCP Servers
CompanyFoundation ModelsMachine LearningForecastingTime SeriesTabular DataSynthetic DataArtificial IntelligencePredictive Analytics

Kin Score

Kin Score Kin Score How this is scored →
scored 2026-07-27 · rubric v0.5
Composite quality — 31.8/100 · thin
Contract Quality 0.0 / 25
Developer Ergonomics 13.5 / 20
Commercial Clarity 6.3 / 20
Operational Transparency 2.7 / 13
Governance 0.0 / 12
Discoverability 9.3 / 10
Agent readiness — 28/100 · agent aware
Machine-Readable Contract 0 / 18
Agentic Access Contract 0 / 15
MCP Server 12 / 12
Machine-Readable Auth 10 / 10
Idempotency 0 / 9
Stable Error Semantics 0 / 8
Request/Response Examples 0 / 7
Rate-Limit Signaling 7 / 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/synthefy: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

APIs 2

Individual APIs this provider publishes, each with its own machine-readable definition.

Synthefy Forecasting API

Direct REST access to Synthefy's foundation models for multivariate time-series forecasting (Migas-1.0), with automatic timestamp/value/metadata handling and exogenous covariate...

Synthefy Nori API

Hosted in-context tabular regression and classification via the Nori foundation model. Predicts on any table in a single forward pass with no training; served over an OpenAI-sty...

MCP Servers 1

Model Context Protocol servers that expose these APIs to AI agents.

synthefy-mcp.yml

MCP SERVER

Rate Limits 1

Documented rate limits and quota policies.

Synthefy Rate Limits

0 limits

RATE LIMITS

Security Posture 2

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

Synthefy Authentication

apiKey/http · 2 schemes

SECURITY

Synthefy Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Get Started 4

Portal, sign-up, and the first successful call

Documentation 2

Reference material describing how the API behaves

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

Design & Contract 3

Pagination, idempotency, versioning, errors, and events

Build 3

SDKs, sample code, and the tooling you integrate with

Access & Security 3

Authentication, authorization, and security posture

Operate 3

Status, limits, changes, and where to get help

Commercial 1

Pricing, plans, and the legal terms of use

Company 2

The organization behind the API

Source (apis.yml)

apis.yml Raw ↑
aid: synthefy
name: Synthefy
x-enrichment:
  date: '2026-07-21'
  status: enriched
  artifacts_added: 11
  pass: local-v1
description: Synthefy builds foundation models for structured data, replacing task-specific machine learning (XGBoost, LightGBM,
  ARIMA, Prophet) with a single API call. Its Nori tabular model performs in-context regression and classification on any
  table with no training, and its time-series Forecasting API (Migas-1.0) delivers multivariate probabilistic forecasts with
  exogenous context. The platform is delivered as a hosted REST API, Python SDKs, Docker containers, AWS SageMaker, and Snowflake,
  serving banking, retail, insurance, healthcare, infrastructure, and marketing use cases with SOC 2 Type II, HIPAA, GDPR,
  and zero-data-retention compliance.
accessModel:
  pricing: unknown
  onboarding: self-serve
  trial: false
  try_now: false
  public: false
  label: Self-serve signup
  confidence: medium
  source:
  - authentication
  generated: '2026-07-22'
  method: derived
image: https://synthefy.com/opengraph-image
url: https://raw.githubusercontent.com/api-evangelist/synthefy/refs/heads/main/apis.yml
x-type: company
x-source: vc-portfolio
x-backed-by:
- wing-venture-capital
x-tier: stub
x-tier-reason: portfolio-lead
specificationVersion: '0.20'
created: '2026-07-17'
modified: '2026-07-21'
tags:
- Company
- Foundation Models
- Machine Learning
- Forecasting
- Time Series
- Tabular Data
- Synthetic Data
- Artificial Intelligence
- Predictive Analytics
apis:
- name: Synthefy Forecasting API
  description: Direct REST access to Synthefy's foundation models for multivariate time-series forecasting (Migas-1.0), with
    automatic timestamp/value/metadata handling and exogenous covariate context. Called via the synthefy Python client.
  humanURL: https://docs.synthefy.com/forecasting-api/overview
  baseURL: https://forecast.synthefy.com
  tags:
  - Forecasting
  - Time Series
  properties:
  - type: GettingStarted
    url: https://docs.synthefy.com/forecasting-api/cloud-quickstart
  - type: APIReference
    url: https://docs.synthefy.com/forecasting-api/overview
- name: Synthefy Nori API
  description: Hosted in-context tabular regression and classification via the Nori foundation model. Predicts on any table
    in a single forward pass with no training; served over an OpenAI-style Bearer-authenticated inference endpoint.
  humanURL: https://docs.synthefy.com/nori/quickstart
  baseURL: https://inference.baseten.co
  tags:
  - Tabular Data
  - Foundation Models
  properties:
  - type: GettingStarted
    url: https://docs.synthefy.com/nori/quickstart
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Website
  url: https://www.synthefy.com/
- type: DeveloperPortal
  url: https://docs.synthefy.com/
- type: Documentation
  url: https://docs.synthefy.com/
- type: APIReference
  url: https://docs.synthefy.com/forecasting-api/overview
- type: GettingStarted
  url: https://docs.synthefy.com/forecasting-api/cloud-quickstart
- type: Blog
  url: https://www.synthefy.com/blog
- type: Support
  url: https://www.synthefy.com/contact
- type: GitHubOrganization
  url: https://github.com/Synthefy
- type: SignUp
  url: https://console.synthefy.com/
- type: Login
  url: https://console.synthefy.com/
- type: PrivacyPolicy
  url: https://www.synthefy.com/privacy
- type: Compliance
  url: https://www.synthefy.com/
- type: Authentication
  url: authentication/synthefy-authentication.yml
- type: Packages
  url: packages/synthefy-packages.yml
- type: SDKs
  url: packages/synthefy-packages.yml
- type: MCPServer
  url: mcp/synthefy-mcp.yml
- type: LLMsTxt
  url: llms/synthefy-llms.txt
- type: Conformance
  url: conformance/synthefy-conformance.yml
- type: Conventions
  url: conventions/synthefy-conventions.yml
- type: RateLimits
  url: rate-limits/synthefy-rate-limits.yml
- type: Lifecycle
  url: lifecycle/synthefy-lifecycle.yml
- type: ChangeLog
  url: changelog/synthefy-changelog.yml
- type: DomainSecurity
  url: security/synthefy-domain-security.yml