Vectorize

Vectorize is a RAG (retrieval-augmented generation) pipeline platform that ingests unstructured data, chunks and embeds it, and serves low-latency retrieval against a managed vector database. The Vectorize API lets developers create, start, and stop RAG pipelines, run retrieval, manage source / destination / AI-platform connectors, upload files, extract documents with Iris, and run deep research.

Vectorize publishes 8 API contracts indexed on the APIs.io network, including AI Platform Connectors API, Destination Connectors API, Extraction API, and 5 more. Tagged areas include Artificial Intelligence, RAG, Vectorization, Embeddings, and Retrieval.

The Vectorize catalog on APIs.io includes 1 Spectral governance ruleset.

Vectorize’s developer surface includes pricing, authentication, documentation, engineering blog, and 10 more developer resources.

🌐 Visit website 📡 Profile data on GitHub

32.4/100 thin ▬ flat Agent 19/100 agent aware Front door AI 4/6 moderate Heartbeat 68/100 alive saas Full breakdown ↓
scored 2026-11-13 · rubric v0.28.0 · Show this score on your site →

AccessPaid

1 published contract

Artificial Intelligence RAGVectorizationEmbeddings Retrieval Vector Search

What this lets a business do 1

Business capabilities this provider's published APIs can perform, derived from its own contracts. Browse all capabilities →

AI Model Services

AE-110

AI Platform Connectors

POST /org/{organizationId}/connectors/aiplatforms

Kin Score

Kin Score How this is scored →
scored 2026-11-13 · rubric v0.28.0

Composite quality — 32.4/100 · thin

Contract Quality 8.7 / 19

Developer Ergonomics 4.8 / 15

Access Clarity 5.1 / 15

Operational Transparency 1.2 / 10

Contract Governance 1.2 / 9

Discoverability 5.0 / 8

Regulatory Posture 0.8 / 15

Create-or-Update Ergonomics 0.0 / 10

Agent readiness — 19/100 · agent aware

Machine-Readable Contract 18 / 18

Agentic Access Contract 10 / 10

Documented Reversibility 0 / 6

MCP Server 0 / 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

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 0 / 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 applies to this provider. This API accepts writes, so it carries 10 points of the composite. It is scored from the published contracts themselves: whether a caller can create-or-update in one call, whether the write accepts a key the caller already holds, and whether the response says which branch ran. Without that, every write needs a search-and-branch in front of it, and the first time that check is skipped a duplicate record is created. Scored against the observed mean rather than raw — a provider at the catalog average is unchanged by this facet, not penalised by it.

The six quality facets above are damped to 75 points between them, because the conditional facet above carries the other 25. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 75% 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):

MCP Server +12 pts — deployment.mode + probe verdict on the mcp/ manifest, not the pointer; an unprobed slug falls back to authorship Ask about this →
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) Ask about this →
Stable Error Semantics +8 pts — OpenAPI $refs a shared error schema across 4xx/5xx responses (verified), else common[].type includes ErrorCatalog / ErrorCodes / DeclineCodes Ask about this →
A2A Agent Card +8 pts — a2a/-a2a.yml manifest, graded on conformance.grade against A2A 1.0.0 Ask about this →
Request/Response Examples +7 pts — share of operations carrying request/response examples; else an Examples / Code Samples link Ask about this →
Registration Without a Human +6 pts — a `registration_endpoint` in the served RFC 8414 / OIDC discovery document Ask about this →

10 more unmet checks in the Agent Readiness table above.

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

Developer Ergonomics scores 32.1 — up to +13.6 composite points Ask about this →
Contract Quality scores 46.2 — up to +13.5 composite points Ask about this →
Access Clarity scores 34.0 — up to +13.2 composite points Ask about this →

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.

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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/vectorize-io/apis.yml: open an issue on github.com/api-evangelist/vectorize-io 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 →

Markets this provider is in provisional

The Kin Score Market layer reads a provider inside its market: its position, and how deep its integrations go. Depth is only comparable within a position. Provisional and unweighted: not part of the Kin Score or agent readiness.

Market	Position	Depth	Registered MCP server	Declares compatibility
Agent Skills (SKILL.md packages)	builds-on	34.5 (thin)	-	1
Zoom App Marketplace and Partner Ecosystem (builders and partners on Zoom)	builds-on	34.5 (thin)	-	1
Obsidian Community Plugins (third-party APIs the Obsidian plugin ecosystem integrates)	builds-on	34.5 (thin)	-	1

Registered MCP server and declares compatibility are report only — not weighted. Undeclared means we found nothing we can read, so there is no number: we never infer integrations.

Standards implemented 1

Standards this provider implements or carries. De facto ones are profiled and measured by the API Commons; formal ones come from the standards directory and are linked by the provider's own tags. The evidence column says how each claim was established — not that it was made.

OpenAPI

measured — observed by APIs.io (published)

APIs 8

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

Vectorize AI Platform Connectors API

Manage AI platform (embedding / model) connectors.

Vectorize Destination Connectors API

Manage destination (vector database) connectors.

Vectorize Extraction API

Vectorize Iris document extraction.

Vectorize Files API

Upload generic files to the platform.

Vectorize Pipelines API

Create and operate RAG pipelines, retrieval, and deep research.

Vectorize Source Connectors API

Manage data source connectors.

Vectorize Uploads API

Push and manage files against File Upload connectors.

Vectorize Workspaces API

List and retrieve workspaces.

Scroll for all 8

Open Collections 9

Open, tool-agnostic API collections (OpenAPI-derived and Bruno).

Vectorize AI Platform Connectors API

OPEN COLLECTION

Vectorize AI Platform Connectors Destination Connectors API

OPEN COLLECTION

Vectorize AI Platform Connectors Extraction API

OPEN COLLECTION

Vectorize AI Platform Connectors Files API

OPEN COLLECTION

Vectorize AI Platform Connectors Pipelines API

OPEN COLLECTION

Vectorize AI Platform Connectors Source Connectors API

OPEN COLLECTION

Vectorize AI Platform Connectors Uploads API

OPEN COLLECTION

Vectorize AI Platform Connectors Workspaces API

OPEN COLLECTION

Vectorize API

OPEN COLLECTION

Scroll for all 9

Vectorize API pricing

Prices published by Vectorize, read 2026-10-07 from vectorize.io/pricing. A free plan or tier is listed.

Plan	Price
Self-hosted	Free Includes: MIT open source license, single Docker command, all four memory networks, Retain/Recall/Reflect APIs
Hindsight Cloud	Pay as you go Includes: Free credits to start; managed infrastructure, automatic scaling, daily backups, dashboard and usage
Retain (store memories)	$10.00 per million tokens
Recall (retrieve memories)	$0.75 per million tokens
Reflect (synthesize patterns)	$0.05 per call
Iris Extract (structured extraction)	$7.50 per million tokens
Mental Model Retrieve	$0.25 per million tokens
Mental Model Refresh	$0.05 per call

All 10 plans, limits and sources →

Rate limits

RAG Pipelines: see plan (1 Free / 3 Starter / 10 Professional / custom Enterprise) pipelines
Pages Processed: see plan (1,500/month Free; higher on paid tiers) pages
Index Update Frequency: see plan (hourly on Professional) schedule

Compiled by API Evangelist, not yet checked against Vectorize's documentation. All 6 limits →

Pricing Plans 1

Published pricing tiers and plan structures.

Vectorize Plans Pricing

10 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Vectorize Rate Limits

6 limits

RATE LIMITS

FinOps 1

Cost, billing, and metering signals for API financial operations.

Vectorize Finops

FINOPS

Spectral Rules 1

Spectral governance rulesets for linting and validating these APIs. Counts are the severity each rule declares, not results of running them.

Vectorize API Rules

64 rules · 60 error-severity 1 warn-severity 3 info-severity

SPECTRAL

Security Posture 2

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

Vectorize Authentication

http · 1 scheme

SECURITY

Vectorize Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Agentic Access (API Evangelist recommendations) 1

Recommended x-agentic-access execution contracts for AI agents.

Vectorize Agentic Access

37 operations · 21 acting · 1 human-in-the-loop

37 operations · 21 acting

AGENTIC

Resources

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Agent Surfaces 1

MCP servers, agent skills, and machine-readable catalogs

AgenticAccess

AgenticAccess

Build 1

SDKs, sample code, and the tooling you integrate with

GitHubOrganization

GitHubOrganization

Access & Security 2

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Authentication

Authentication

Operate 1

Status, limits, changes, and where to get help

RateLimits

RateLimits

Commercial 3

Pricing, plans, and the legal terms of use

Pricing

Pricing

Plans

Plans

FinOps

FinOps

Company 4

The organization behind the API

BlogRSS

BlogRSS

LinkedIn

Website

Website

Blog

Blog

Other 1

Properties that don't map to a standard resource type

CapabilityMap

CapabilityMap

Source (apis.yml)

aid: vectorize-io
url: https://raw.githubusercontent.com/api-evangelist/vectorize-io/refs/heads/main/apis.yml
name: Vectorize
kind: company
description: Vectorize is a RAG (retrieval-augmented generation) pipeline platform that ingests unstructured data, chunks
  and embeds it, and serves low-latency retrieval against a managed vector database. The Vectorize API lets developers create,
  start, and stop RAG pipelines, run retrieval, manage source / destination / AI-platform connectors, upload files, extract
  documents with Iris, and run deep research.
deliveryModel:
  model: saas
  open_source: false
  commercial: true
  callable_host: true
  label: Hosted service · you call their endpoint
  confidence: high
  source:
  - openapi
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: paid
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Paid
  confidence: medium
  source:
  - plans
  - authentication
  - security
  generated: '2026-11-13'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/vectorize-io.png
x-docs-platform: docusaurus
x-docs-platform-confidence: medium
x-docs-platform-checked: 2026-10-17
x-docs-hosting: vercel
tags:
- Artificial Intelligence
- RAG
- Vectorization
- Embeddings
- Retrieval
- Vector Search
tags_raw:
- AI
- RAG
- Vectorization
- Embeddings
- Retrieval
- Vector Database
created: '2026-06-20'
modified: '2026-10-06'
specificationVersion: '0.23'
apis:
- aid: vectorize-io:vectorize-io-ai-platform-connectors-api
  name: Vectorize AI Platform Connectors API
  description: Manage AI platform (embedding / model) connectors.
  humanURL: https://docs.vectorize.io/reference/api/api-getting-started/
  baseURL: https://api.vectorize.io/v1
  tags:
  - AI Platform Connectors
  properties:
  - type: OpenAPI
    url: openapi/vectorize-io-ai-platform-connectors-api-openapi.yml
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/
  - type: APIReference
    url: https://docs.vectorize.io/reference/api/api-getting-started/
  - type: PostmanCollection
    url: collections/vectorize-io.postman_collection.json
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/retrieval-endpoint/
  - type: Documentation
    url: https://docs.vectorize.io/integrations/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-sources/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/extract-information/understanding-iris/
- aid: vectorize-io:vectorize-io-destination-connectors-api
  name: Vectorize Destination Connectors API
  description: Manage destination (vector database) connectors.
  humanURL: https://docs.vectorize.io/reference/api/api-getting-started/
  baseURL: https://api.vectorize.io/v1
  tags:
  - Destination Connectors
  properties:
  - type: OpenAPI
    url: openapi/vectorize-io-destination-connectors-api-openapi.yml
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/
  - type: APIReference
    url: https://docs.vectorize.io/reference/api/api-getting-started/
  - type: PostmanCollection
    url: collections/vectorize-io.postman_collection.json
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/retrieval-endpoint/
  - type: Documentation
    url: https://docs.vectorize.io/integrations/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-sources/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/extract-information/understanding-iris/
- aid: vectorize-io:vectorize-io-extraction-api
  name: Vectorize Extraction API
  description: Vectorize Iris document extraction.
  humanURL: https://docs.vectorize.io/reference/api/api-getting-started/
  baseURL: https://api.vectorize.io/v1
  tags:
  - Extraction
  properties:
  - type: OpenAPI
    url: openapi/vectorize-io-extraction-api-openapi.yml
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/
  - type: APIReference
    url: https://docs.vectorize.io/reference/api/api-getting-started/
  - type: PostmanCollection
    url: collections/vectorize-io.postman_collection.json
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/retrieval-endpoint/
  - type: Documentation
    url: https://docs.vectorize.io/integrations/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-sources/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/extract-information/understanding-iris/
- aid: vectorize-io:vectorize-io-files-api
  name: Vectorize Files API
  description: Upload generic files to the platform.
  humanURL: https://docs.vectorize.io/reference/api/api-getting-started/
  baseURL: https://api.vectorize.io/v1
  tags:
  - File
  tags_raw:
  - Files
  properties:
  - type: OpenAPI
    url: openapi/vectorize-io-files-api-openapi.yml
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/
  - type: APIReference
    url: https://docs.vectorize.io/reference/api/api-getting-started/
  - type: PostmanCollection
    url: collections/vectorize-io.postman_collection.json
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/retrieval-endpoint/
  - type: Documentation
    url: https://docs.vectorize.io/integrations/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-sources/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/extract-information/understanding-iris/
- aid: vectorize-io:vectorize-io-pipelines-api
  name: Vectorize Pipelines API
  description: Create and operate RAG pipelines, retrieval, and deep research.
  humanURL: https://docs.vectorize.io/reference/api/api-getting-started/
  baseURL: https://api.vectorize.io/v1
  tags:
  - Pipelines
  properties:
  - type: OpenAPI
    url: openapi/vectorize-io-pipelines-api-openapi.yml
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/
  - type: APIReference
    url: https://docs.vectorize.io/reference/api/api-getting-started/
  - type: PostmanCollection
    url: collections/vectorize-io.postman_collection.json
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/retrieval-endpoint/
  - type: Documentation
    url: https://docs.vectorize.io/integrations/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-sources/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/extract-information/understanding-iris/
- aid: vectorize-io:vectorize-io-source-connectors-api
  name: Vectorize Source Connectors API
  description: Manage data source connectors.
  humanURL: https://docs.vectorize.io/reference/api/api-getting-started/
  baseURL: https://api.vectorize.io/v1
  tags:
  - Source Connectors
  properties:
  - type: OpenAPI
    url: openapi/vectorize-io-source-connectors-api-openapi.yml
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/
  - type: APIReference
    url: https://docs.vectorize.io/reference/api/api-getting-started/
  - type: PostmanCollection
    url: collections/vectorize-io.postman_collection.json
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/retrieval-endpoint/
  - type: Documentation
    url: https://docs.vectorize.io/integrations/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-sources/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/extract-information/understanding-iris/
- aid: vectorize-io:vectorize-io-uploads-api
  name: Vectorize Uploads API
  description: Push and manage files against File Upload connectors.
  humanURL: https://docs.vectorize.io/reference/api/api-getting-started/
  baseURL: https://api.vectorize.io/v1
  tags:
  - Uploads
  properties:
  - type: OpenAPI
    url: openapi/vectorize-io-uploads-api-openapi.yml
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/
  - type: APIReference
    url: https://docs.vectorize.io/reference/api/api-getting-started/
  - type: PostmanCollection
    url: collections/vectorize-io.postman_collection.json
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/retrieval-endpoint/
  - type: Documentation
    url: https://docs.vectorize.io/integrations/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-sources/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/extract-information/understanding-iris/
- aid: vectorize-io:vectorize-io-workspaces-api
  name: Vectorize Workspaces API
  description: List and retrieve workspaces.
  humanURL: https://docs.vectorize.io/reference/api/api-getting-started/
  baseURL: https://api.vectorize.io/v1
  tags:
  - Workspace
  tags_raw:
  - Workspaces
  properties:
  - type: OpenAPI
    url: openapi/vectorize-io-workspaces-api-openapi.yml
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/
  - type: APIReference
    url: https://docs.vectorize.io/reference/api/api-getting-started/
  - type: PostmanCollection
    url: collections/vectorize-io.postman_collection.json
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-pipelines/retrieval-endpoint/
  - type: Documentation
    url: https://docs.vectorize.io/integrations/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/data-sources/
  - type: Documentation
    url: https://docs.vectorize.io/build-deploy/extract-information/understanding-iris/
common:
- type: CapabilityMap
  url: capabilities/vectorize-io-capability-edges.yml
  name: Vectorize Business Capability Map
- type: Pricing
  url: https://vectorize.io/pricing
- url: https://vectorize.io/feed.xml
  type: BlogRSS
- type: AgenticAccess
  url: agentic-access/vectorize-io-agentic-access.yml
- type: DomainSecurity
  url: security/vectorize-io-domain-security.yml
- type: Authentication
  url: authentication/vectorize-io-authentication.yml
- type: GitHubOrganization
  url: https://github.com/vectorize-io
- type: LinkedIn
  url: https://www.linkedin.com/company/vectorize-io
- type: Website
  url: https://vectorize.io/
- type: Documentation
  url: https://docs.vectorize.io
- type: Plans
  url: plans/vectorize-io-plans-pricing.yml
- type: RateLimits
  url: rate-limits/vectorize-io-rate-limits.yml
- type: FinOps
  url: finops/vectorize-io-finops.yml
- type: Blog
  url: https://blog.vectorize.io/feed/
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com

Vectorize API — frequently asked questions

Does Vectorize have an API?

Yes. APIs.io lists 8 APIs from Vectorize, including Vectorize AI Platform Connectors API, Vectorize Destination Connectors API and Vectorize Extraction API, and 5 more.

Is there an OpenAPI specification for the Vectorize API?

Yes. APIs.io indexes 8 OpenAPI specifications for Vectorize, each linked for download from this page.

How do I authenticate with the Vectorize API?

Vectorize uses bearer-token authentication (http · 1 scheme). The details are profiled on APIs.io as Vectorize Authentication.

How much does the Vectorize API cost?

Vectorize publishes its prices; its Hindsight Cloud plan is Pay as you go as of 2026-10-07. APIs.io lists 10 pricing plans for Vectorize, with each plan's price, limits and inclusions under Pricing on this page.

Is the Vectorize API ready for AI agents?

Vectorize has a Kin Score of 32.4 out of 100 (thin) and an Agent Readiness score of 19.0 (agent-aware), scored by API Evangelist on 2026-11-13.

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