Voyage AI

Voyage AI builds state-of-the-art embedding and reranker models for retrieval-augmented generation (RAG) and semantic search. The platform exposes an OpenAI-style REST API at api.voyageai.com/v1 for text embeddings, multimodal embeddings, contextualized embeddings, and reranking, with Python and TypeScript SDKs. Model families include voyage-3.x and voyage-4.x text embeddings, voyage-code-3, domain-specialised models (voyage-finance-2, voyage-law-2), voyage-multimodal-3, and the voyage-rerank-2 reranker family. Voyage AI was acquired by MongoDB in February 2024 and is integrated into MongoDB Atlas Vector Search; models are also distributed via AWS Marketplace, Azure Marketplace, and Snowflake.

Voyage AI publishes 4 APIs on the APIs.io network, including Contextualized API, Embeddings API, Multimodal API, and 1 more. Tagged areas include Embeddings, Rerankers, RAG, Semantic Search, and AI Models.

Voyage AI’s developer surface includes documentation, GitHub presence, pricing, engineering blog, and 10 more developer resources.

🌐 Visit website 📡 Source on GitHub

32.9/100 thin ▬ flat Agent 18/100 agent aware open core · MIT Full breakdown ↓
scored 2026-09-14 · rubric v0.22.0

AccessFree

1 APIs

EmbeddingsRerankersRAG Semantic Search AI Models Vector Search Multi-Modal

Kin Score

Kin Score How this is scored →
scored 2026-09-14 · rubric v0.22.0

Composite quality — 32.9/100 · thin

Contract Quality 10.3 / 20

Developer Ergonomics 1.1 / 16

Access Clarity 6.3 / 16

Operational Transparency 4.4 / 10

Contract Governance 0.0 / 10

Discoverability 5.5 / 8

Open Source Surface 2.5 / 10

Create-or-Update Ergonomics 0.0 / 10

Agent readiness — 18/100 · agent aware

Machine-Readable Contract 18 / 18

Agentic Access Contract 0 / 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

Open Source Surface applies to this provider. This product is open source and we read its repository directly, so Open Source Surface carries 10 points of the composite. It is scored from what the repository actually publishes — a security policy, a contribution guide, a release history, a code of conduct — read live from the provider rather than inferred from our own catalog pointers. This facet adds; nothing was taken away to make room for it. An open-source project is not excused from the commercial facets, because exemption would strip it of the points it does earn. If we have the wrong repository, or this product is not open source, say so on your provider repo and we will drop the facet rather than have you publish against 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 80 points between them, because the conditional facet above carries the other 20. That is why each facet's contribution is shown against a damped maximum: raising a quality facet moves the composite by 80% of its nominal weight, not 100%. The full arithmetic is at apis.io/rating/.

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/voyage-ai: 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 →

Standards implemented 1

Interfaces this provider implements that became standards by being copied rather than ratified. Each is profiled by the API Commons, and the evidence column says how the claim was established — not that it was made.

The OpenAI Interface

declared — publishes a spec that declares them

2 core of 338 operations graded · api-commons/models

APIs 9

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

Voyage AI Rerank API

Reranking endpoint that scores a list of candidate documents against a query and returns relevance scores. Powered by the voyage-rerank-2 model family, used downstream of vector...

Voyage AI Multimodal Embeddings API

Multimodal embeddings endpoint backed by voyage-multimodal-3 that accepts interleaved text and images in a single request and returns embeddings in a shared vector space, enabli...

Voyage AI Contextualized Embeddings API

Endpoint that embeds chunks while conditioning on surrounding document context, improving recall for long-document RAG workflows where chunk embeddings would otherwise lose docu...

Voyage AI Python SDK

Official Python client (voyageai) wrapping the embeddings, multimodal, contextualized, and reranking endpoints with batching, retries, and async support.

Voyage AI TypeScript SDK

Official TypeScript / JavaScript client for the Voyage AI REST API.

Voyage AI Contextualized API

Embed chunks conditioned on surrounding document context.

Voyage AI Embeddings API

Dense text embeddings.

Voyage AI Multimodal API

Embed interleaved text and images in a shared vector space.

Voyage AI Rerank API

Cross-encoder reranking of candidate documents.

Scroll for all 9

Open Collections 5

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

API Collection

OPEN COLLECTION

Voyage AI Contextualized API

OPEN COLLECTION

Voyage AI Embeddings API

OPEN COLLECTION

Voyage AI Multimodal API

OPEN COLLECTION

Voyage AI Rerank API

OPEN COLLECTION

Pricing Plans 1

Published pricing tiers and plan structures.

Voyage Ai Plans Pricing

1 plans

PLANS

Rate Limits 1

Documented rate limits and quota policies.

Voyage Ai Rate Limits

2 limits

RATE LIMITS

FinOps 1

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

Voyage Ai Finops

FINOPS

Security Posture 1

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

Voyage Ai Domain Security

TLSv1.3 · HSTS · DMARC

SECURITY

Resources

Documentation 1

Reference material describing how the API behaves

Documentation

Documentation

Build 1

SDKs, sample code, and the tooling you integrate with

GitHub

GitHub

Access & Security 1

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Operate 3

Status, limits, changes, and where to get help

IssueTracker

IssueTracker

Releases

Releases

RateLimits

RateLimits

Commercial 4

Pricing, plans, and the legal terms of use

License

Pricing

Plans

FinOps

Company 3

The organization behind the API

LinkedIn

Website

Website

Blog

Blog

Other 1

Properties that don't map to a standard resource type

Parent

Parent

Source (apis.yml)

aid: voyage-ai
url: https://raw.githubusercontent.com/api-evangelist/voyage-ai/refs/heads/main/apis.yml
name: Voyage AI
kind: company
description: Voyage AI builds state-of-the-art embedding and reranker models for retrieval-augmented generation (RAG) and
  semantic search. The platform exposes an OpenAI-style REST API at api.voyageai.com/v1 for text embeddings, multimodal embeddings,
  contextualized embeddings, and reranking, with Python and TypeScript SDKs. Model families include voyage-3.x and voyage-4.x
  text embeddings, voyage-code-3, domain-specialised models (voyage-finance-2, voyage-law-2), voyage-multimodal-3, and the
  voyage-rerank-2 reranker family. Voyage AI was acquired by MongoDB in February 2024 and is integrated into MongoDB Atlas
  Vector Search; models are also distributed via AWS Marketplace, Azure Marketplace, and Snowflake.
deliveryModel:
  model: open-core
  license: MIT
  open_source: true
  commercial: true
  callable_host: true
  label: Open core · an OSS project plus a commercial hosted product
  confidence: high
  source:
  - license
  - openapi
  - pricing
  generated: '2026-08-28'
  method: derived
accessModel:
  pricing: free
  onboarding: unknown
  trial: false
  try_now: false
  public: false
  label: Free
  confidence: medium
  source:
  - plans
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/voyage-ai.png
tags:
- Embeddings
- Rerankers
- RAG
- Semantic Search
- AI Models
- Vector Search
- Multi-Modal
tags_raw:
- Embeddings
- Rerankers
- RAG
- Semantic Search
- AI Models
- Vector Search
- Multimodal
created: '2026-05-23'
modified: '2026-05-23'
specificationVersion: '0.23'
apis:
- aid: voyage-ai:rerank
  name: Voyage AI Rerank API
  description: Reranking endpoint that scores a list of candidate documents against a query and returns relevance scores.
    Powered by the voyage-rerank-2 model family, used downstream of vector search to improve retrieval precision in RAG pipelines.
  humanURL: https://docs.voyageai.com/reference/reranker-api
  baseURL: https://api.voyageai.com/v1
  tags:
  - Rerank
  - Retrieval
  - RAG
  properties:
  - type: Documentation
    url: https://docs.voyageai.com/reference/reranker-api
- aid: voyage-ai:multimodal-embeddings
  name: Voyage AI Multimodal Embeddings API
  description: Multimodal embeddings endpoint backed by voyage-multimodal-3 that accepts interleaved text and images in a
    single request and returns embeddings in a shared vector space, enabling cross-modal retrieval for documents that mix
    text, screenshots, charts, and figures.
  humanURL: https://docs.voyageai.com/reference/multimodal-embeddings-api
  baseURL: https://api.voyageai.com/v1
  tags:
  - Embeddings
  - Multi-Modal
  - Vision
  tags_raw:
  - Embeddings
  - Multimodal
  - Vision
  properties:
  - type: Documentation
    url: https://docs.voyageai.com/reference/multimodal-embeddings-api
- aid: voyage-ai:contextualized-embeddings
  name: Voyage AI Contextualized Embeddings API
  description: Endpoint that embeds chunks while conditioning on surrounding document context, improving recall for long-document
    RAG workflows where chunk embeddings would otherwise lose document-level signal.
  humanURL: https://docs.voyageai.com/reference/contextualized-embeddings-api
  baseURL: https://api.voyageai.com/v1
  tags:
  - Embeddings
  - Contextualized
  - RAG
  properties:
  - type: Documentation
    url: https://docs.voyageai.com/reference/contextualized-embeddings-api
- aid: voyage-ai:python-sdk
  name: Voyage AI Python SDK
  description: Official Python client (voyageai) wrapping the embeddings, multimodal, contextualized, and reranking endpoints
    with batching, retries, and async support.
  humanURL: https://github.com/voyage-ai/voyageai-python
  baseURL: https://github.com/voyage-ai/voyageai-python
  tags:
  - SDK
  - Python
  properties:
  - type: Repository
    url: https://github.com/voyage-ai/voyageai-python
  - type: Package
    url: https://pypi.org/project/voyageai/
- aid: voyage-ai:typescript-sdk
  name: Voyage AI TypeScript SDK
  description: Official TypeScript / JavaScript client for the Voyage AI REST API.
  humanURL: https://github.com/voyage-ai/typescript-sdk
  baseURL: https://github.com/voyage-ai/typescript-sdk
  tags:
  - SDK
  - TypeScript
  - JavaScript
  properties:
  - type: Repository
    url: https://github.com/voyage-ai/typescript-sdk
- aid: voyage-ai:voyage-ai-contextualized-api
  name: Voyage AI Contextualized API
  description: Embed chunks conditioned on surrounding document context.
  humanURL: https://docs.voyageai.com/reference/embeddings-api
  baseURL: https://api.voyageai.com/v1
  tags:
  - Contextualized
  properties:
  - type: OpenAPI
    url: openapi/voyage-ai-contextualized-api-openapi.yml
  - type: Documentation
    url: https://docs.voyageai.com/reference/embeddings-api
- aid: voyage-ai:voyage-ai-embeddings-api
  name: Voyage AI Embeddings API
  description: Dense text embeddings.
  humanURL: https://docs.voyageai.com/reference/embeddings-api
  baseURL: https://api.voyageai.com/v1
  tags:
  - Embeddings
  properties:
  - type: OpenAPI
    url: openapi/voyage-ai-embeddings-api-openapi.yml
  - type: Documentation
    url: https://docs.voyageai.com/reference/embeddings-api
- aid: voyage-ai:voyage-ai-multimodal-api
  name: Voyage AI Multimodal API
  description: Embed interleaved text and images in a shared vector space.
  humanURL: https://docs.voyageai.com/reference/embeddings-api
  baseURL: https://api.voyageai.com/v1
  tags:
  - Multi-Modal
  tags_raw:
  - Multimodal
  properties:
  - type: OpenAPI
    url: openapi/voyage-ai-multimodal-api-openapi.yml
  - type: Documentation
    url: https://docs.voyageai.com/reference/embeddings-api
- aid: voyage-ai:voyage-ai-rerank-api
  name: Voyage AI Rerank API
  description: Cross-encoder reranking of candidate documents.
  humanURL: https://docs.voyageai.com/reference/embeddings-api
  baseURL: https://api.voyageai.com/v1
  tags:
  - Rerank
  properties:
  - type: OpenAPI
    url: openapi/voyage-ai-rerank-api-openapi.yml
  - type: Documentation
    url: https://docs.voyageai.com/reference/embeddings-api
common:
- type: IssueTracker
  url: https://github.com/voyage-ai/voyageai-python/issues
- type: Releases
  url: https://github.com/voyage-ai/voyageai-python/releases
- type: License
  name: MIT
  url: https://github.com/voyage-ai/voyageai-python/blob/main/LICENSE
- type: DomainSecurity
  url: security/voyage-ai-domain-security.yml
- type: LinkedIn
  url: https://www.linkedin.com/company/voyage-ai
- type: Website
  url: https://www.voyageai.com/
- type: Documentation
  url: https://docs.voyageai.com/
- type: GitHub
  url: https://github.com/voyage-ai
- type: Pricing
  url: https://docs.voyageai.com/docs/pricing
- type: Parent
  url: https://www.mongodb.com/
- type: Plans
  url: plans/voyage-ai-plans-pricing.yml
- type: RateLimits
  url: rate-limits/voyage-ai-rate-limits.yml
- type: FinOps
  url: finops/voyage-ai-finops.yml
- url: https://blog.voyageai.com/feed
  type: Blog
integrations:
- name: MongoDB Atlas Vector Search
- name: AWS Marketplace
- name: Azure Marketplace
- name: Snowflake
- name: LangChain
- name: LlamaIndex
- name: Haystack
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com

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