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 8 more developer resources.

🌐 Visit website 📡 Source on GitHub

33.1/100 thin ▬ flat Agent 18/100 agent aware Full breakdown ↓
scored 2026-08-25 · rubric v0.14.0

AccessFree

9 APIs

EmbeddingsRerankersRAG Semantic Search AI Models Vector Search Multi-Modal

Kin Score

Kin Score How this is scored →
scored 2026-08-25 · rubric v0.14.0

Composite quality — 33.1/100 · thin

Contract Quality 12.9 / 25

Developer Ergonomics 1.4 / 20

Access Clarity 7.9 / 20

Operational Transparency 3.4 / 13

Contract Governance 0.0 / 12

Discoverability 7.4 / 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 Surface 0 / 5

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/voyage-ai: 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 9

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

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.

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 1

Status, limits, changes, and where to get help

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.
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: 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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APIs 9

Voyage AI Rerank API

Voyage AI Multimodal Embeddings API

Voyage AI Contextualized Embeddings API

Voyage AI Python SDK

Voyage AI TypeScript SDK

Voyage AI Contextualized API

Voyage AI Embeddings API

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Voyage AI Rerank API

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