Product

Voyage Embeddings

by Voyage AI

Product website
https://www.voyageai.com/
Documentation
https://docs.voyageai.com/
Pricing
https://docs.voyageai.com/docs/pricing
Categories
Semantic Search / RAG

Description

Text and multimodal embedding and reranking models for high-precision search and retrieval in RAG pipelines.

AI-native score

How ready this product is for agents to use, on a 0–100 scale across four weighted dimensions. Security is one of them, so a high score is not a substitute for your own security or vendor-risk review. How is this scored?

Unrated. Only 38% of the scored decision fields are researched, so the grade is held until more are confirmed. The breakdown below shows what's been scored.

Integration1/10Trust2/6Portability4/4Security0/4Tier D34/100
Component Raw Weight Contribution
Integration 1/10 35% 3.5
Trust 2/6 30% 10.0
Portability 4/4 20% 20.0
Security 0/4 15% 0.0
Signals that fired
  • Integration: SDK / developer kit (+1)
  • Trust: Zero data retention (available, +1) ; No generative AI training (available, +1)
  • Portability: Standard protocol access (+1) ; No proprietary-SDK lock-in (+1) ; Self-hostable (+1) ; Open source (+1)
Signals not researched

These gaps cover the fields used in the AI-native score.

  • Integration surfaces: llms.txt, Headless signup, MCP servers, Native connectors, API specs, Agent skills
  • Trust & data policy: Trust center, Multi-factor authentication, Hard budget caps, Sandbox environment, Data export, Data import, Open standards, Documented provider swap
  • Security & compliance: Compliance certifications, Access controls

Trust & data policy

Zero data retention
Available
No generative AI training
Available
Standard protocol access
Yes
No proprietary-SDK lock-in
Yes
Self-hostable
Yes
Open source
Yes
Self-hosting guide
https://github.com/voyage-ai/voyageai-python#local-models-voyage-4-nano

Not yet researched Trust center, Multi-factor authentication, Hard budget caps, Sandbox environment, Data export, Data import, Open standards, Documented provider swap

What it does

Capabilities

  • Text embedding

    Convert text into vector representations for semantic search and retrieval.

    View 2 products

Jobs to be done

  • Embed text for retrieval

    Generate embeddings to retrieve relevant documents for a query.

    View 2 products

Integration surfaces

How an agent connects to this product and finds its documentation. The largest dimension of the AI-native score (35%).

WebMCP
No

Developer kits

Confirmed absent Agent2Agent (A2A) servers , Command-line interfaces

Not yet researched llms.txt, Headless signup, MCP servers, Native connectors, API specs, Agent skills

Offers

Full pricing page

voyage-4

Rate Unit price
voyage-4 $0.06 per 1,000,000 tokens

First 200 million tokens are free for each account; subsequent standard endpoint usage uses the stated rate. Batch pricing differs.

Reviews

No approved reviews yet.

RSS: approved reviews

Catalog activity

Track how this entry changes as proposals are opened and merged.

RSS: merged changes · RSS: open proposals

Products from other publishers that share a job-to-be-done or category, most-shared first.

  • Nomic Atlas by Nomic Unrated

    Same job: Embed text for retrieval (not assessed)

  • Pinecone by Pinecone Unrated
    Semantic Search / RAG Vector Databases
  • Marqo by Marqo Unrated
    Semantic Search / RAG

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Voyage Embeddings — listed on Open Agent Guide Voyage Embeddings — listed on Open Agent Guide

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Ready to decide?

Unrated · 38% researched. Grade withheld until more fields are verified.

Visit Voyage Embeddings