Continual

Continual was an operational-AI / MLOps platform for the modern data stack, founded by Tristan Zajonc (previously Sense, acquired by Cloudera) and Tyler Kohn (co-founder of RichRelevance). It let data and analytics teams declaratively build, deploy, and continuously maintain production predictive models directly inside cloud data warehouses — Snowflake, Databricks, and BigQuery — using SQL and dbt as the primary interface rather than bespoke ML pipelines. The company raised a seed round led by Amplify Partners and a $14.5M Series A in 2022. The product is now dormant: continual.ai is a parked single-page shell, the documentation host redirects to the homepage, and the last release of the first-party Python CLI + SDK on PyPI was in March 2023. This profile captures the verifiable public artifacts that remain — the PyPI package, the GitHub organization, and a live domain-security posture.

Continual is profiled on the APIs.io network. Tagged areas include Company, Developer Tools, Machine Learning, MLOps, and Artificial Intelligence.

Continual’s developer surface includes pricing, CLI, and 9 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

14.7/100 emerging ▬ flat Agent 0/100 human only Front door AI 4/6 moderate Heartbeat 100/100 alive library Full breakdown ↓
scored 2026-11-06 · rubric v0.27.0 · Show this score on your site →

AccessFreemium

0 APIs

Company Developer Tools Machine Learning MLOps Artificial Intelligence DataModern Data StackSnowflake SQL

Kin Score

Kin Score How this is scored →
scored 2026-11-06 · rubric v0.27.0

Composite quality — 14.7/100 · emerging

Contract Quality 0.0 / 21

Developer Ergonomics 2.4 / 17

Access Clarity 6.3 / 17

Operational Transparency 0.3 / 11

Contract Governance 0.0 / 10

Discoverability 4.7 / 9

Regulatory Posture 0.8 / 15

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

Pagination 5 / 5

Distinct Operations 3 / 3

MCP Tool Quality 6 / 6

Regulatory Posture applies to this provider. Its tags matched the Horizontal (data, software, accessibility, platform) regime, so Regulatory Posture carries 15 points of the composite. If this regime is wrong for your business, say so on your provider repo — the applicability map is public and we will correct it.

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.

The six quality facets above are damped to 85 points between them, because the conditional facet above carries the other 15. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 85% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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Agent readiness — checks not met, largest first (exact, from this profile):

Machine-Readable Contract +18 pts — api_specs includes an OpenAPI document
MCP Server +12 pts — deployment.mode + probe verdict on the mcp/ manifest, not the pointer; an unprobed slug falls back to authorship
Agentic Access Contract +10 pts — agentic_access artifact present (x-agentic-access), graded by author
Machine-Readable Auth +10 pts — a served openid-configuration/oauth-authorization-server carrying `issuer` (served), else the securitySchemes class in the provider OpenAPIs — bound (mutualTLS, DPoP, Signature) > negotiable (oauth2 authorizationCode/clientCredentials, openIdConnect) > bearer (http bearer, apiKey)
Idempotency +9 pts — OpenAPI mutating operations declare an idempotency key — a header, a request-body property, or a named de-duplication token whose own description says so (verified); else common[].type matches /idempoten/i (documented)
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes

13 more unmet checks in the Agent Readiness table above.

Kin Score — facets with the most composite points still available (weight × headroom):

Contract Quality scores 0.0 — up to +25.0 composite points
Developer Ergonomics scores 14.3 — up to +17.1 composite points
Operational Transparency scores 2.6 — up to +12.7 composite points

Each check links to what satisfies it. Publish the artifact, or tell us where it already lives, and the score moves on the next scoring run.

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 the provider profile at artifacts.apis.io/continual/apis.yml: open an issue on github.com/api-evangelist/continual to ask a question or point us at an artifact you publish. Submit an artifact on GitHub — free → Manage your own listing — the Influence plan, $499/mo →

Continual API pricing

Prices published by Continual, read 2026-10-07 from continual.ai/pricing.

Plan	Price
Free	$0/month Includes: One project, $10 in starter credits, unlimited collaborators, no credit card required
Business	$100/month Includes: Everything in Free, plus $100 in monthly credits, one shared workspace balance, unlimited projects,
Enterprise	Custom Includes: Everything in Business, plus more than $5,000 in monthly credits, SAML SSO and SCIM, white-glove onb

Plan details, limits and sources →

Pricing Plans 1

Published pricing tiers and plan structures.

Continual Plans Pricing

3 plans

PLANS

Security Posture 1

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

Continual Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

LLMsTxt

LLMsTxt

WellKnown

WellKnown

Build 5

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

Packages

SDKs

CLI

SourceCode

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Commercial 2

Pricing, plans, and the legal terms of use

Pricing

Pricing

Plans

Plans

Company 1

The organization behind the API

Website

Website

Source (apis.yml)

aid: continual
name: Continual
description: 'Continual was an operational-AI / MLOps platform for the modern data stack, founded by Tristan Zajonc (previously
  Sense, acquired by Cloudera) and Tyler Kohn (co-founder of RichRelevance). It let data and analytics teams declaratively
  build, deploy, and continuously maintain production predictive models directly inside cloud data warehouses — Snowflake,
  Databricks, and BigQuery — using SQL and dbt as the primary interface rather than bespoke ML pipelines. The company raised
  a seed round led by Amplify Partners and a $14.5M Series A in 2022. The product is now dormant: continual.ai is a parked
  single-page shell, the documentation host redirects to the homepage, and the last release of the first-party Python CLI
  + SDK on PyPI was in March 2023. This profile captures the verifiable public artifacts that remain — the PyPI package, the
  GitHub organization, and a live domain-security posture.'
url: https://raw.githubusercontent.com/api-evangelist/continual/refs/heads/main/apis.yml
deliveryModel:
  model: library
  open_source: false
  commercial: false
  callable_host: false
  label: Library · distributed through package registries, no callable service
  confidence: low
  source:
  - none
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: freemium
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Freemium
  confidence: low
  source:
  - plans
  - security
  generated: '2026-11-06'
  method: derived
image: https://continual.ai/favicon.svg
x-type: company
x-source: vc-portfolio
x-backed-by:
- amplify-partners
x-tier: stub
x-tier-reason: portfolio-lead
x-status: dormant
x-status-reason: Website is a parked shell; last PyPI release 2023-03-22; no live API or docs.
specificationVersion: '0.23'
created: '2026-07-17'
modified: '2026-07-18'
tags:
- Company
- Developer Tools
- Machine Learning
- MLOps
- Artificial Intelligence
- Data
- Modern Data Stack
- Snowflake
- SQL
tags_raw:
- Company
- Developer Tools
- Machine Learning
- MLOps
- Artificial Intelligence
- Data
- Modern Data Stack
- Snowflake
- SQL
- Machine-Learning
apis: []
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com
- FN: APIs.json
  email: info@apis.io
common:
- type: Pricing
  url: https://continual.ai/pricing
- type: Plans
  url: plans/continual-plans-pricing.yml
- type: Website
  url: https://continual.ai
- type: GitHubOrganization
  url: https://github.com/continual-ai
- type: Packages
  url: packages/continual-packages.yml
- type: SDKs
  url: packages/continual-packages.yml
- type: CLI
  url: cli/continual-cli.yml
- type: SourceCode
  url: https://pypi.org/project/continual/
- type: LLMsTxt
  url: llms/continual-llms.txt
- type: WellKnown
  url: well-known/continual-well-known.yml
- type: DomainSecurity
  url: security/continual-domain-security.yml
x-enrichment:
  date: '2026-07-19'
  status: backfilled
  pass: local-v1
  note: backfilled from .gitignore signal + verified work evidence

Continual API — frequently asked questions

How much does the Continual API cost?

Continual publishes its prices; its Free plan is $0/month as of 2026-10-07. APIs.io lists 3 pricing plans for Continual, with each plan's price, limits and inclusions under Pricing on this page.

Is the Continual API ready for AI agents?

Continual has a Kin Score of 14.7 out of 100 (emerging) and an Agent Readiness score of 0.0 (human-only), scored by API Evangelist on 2026-11-06.

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