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About

Weaviate is an open-source, AI-native vector database for building search, RAG, and agentic AI applications. Store data objects alongside vector embeddings from your favorite ML models and scale seamlessly into billions of objects. Bring your own vectors or use built-in vectorization, then combine vector, keyword, and hybrid search for state-of-the-art results, even with filters. Pipe results through leading LLMs to power next-generation, retrieval-augmented experiences. Weaviate goes beyond the database: the Query Agent turns natural language into precise, cited queries, Engram provides managed memory for AI agents, and Weaviate Embeddings handles vectorization for you. Run it yourself under an open-source license, or use fully managed Weaviate Cloud on AWS, GCP, or Azure, with SOC 2 Type II compliance, multi-tenancy, and RBAC built in. Use any generative model with your own data to build chatbots, semantic search, recommendation, and agentic workflows.

About

Voyage AI introduces voyage-code-3, a next-generation embedding model optimized for code retrieval. It outperforms OpenAI-v3-large and CodeSage-large by an average of 13.80% and 16.81% on a suite of 32 code retrieval datasets, respectively. It supports embeddings of 2048, 1024, 512, and 256 dimensions and offers multiple embedding quantization options, including float (32-bit), int8 (8-bit signed integer), uint8 (8-bit unsigned integer), binary (bit-packed int8), and ubinary (bit-packed uint8). With a 32 K-token context length, it surpasses OpenAI's 8K and CodeSage Large's 1K context lengths. Voyage-code-3 employs Matryoshka learning to create embeddings with a nested family of various lengths within a single vector. This allows users to vectorize documents into a 2048-dimensional vector and later use shorter versions (e.g., 256, 512, or 1024 dimensions) without re-invoking the embedding model.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers and AI teams building search, RAG, and agentic AI applications

Audience

AI researchers and developers in search of a solution providing an embedding model for code retrieval

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Open source (free); free Weaviate Cloud tier; paid Cloud plans from $45/mo.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Weaviate
Founded: 2019
The Netherlands
weaviate.io

Company Information

MongoDB
Founded: 2007
United States
blog.voyageai.com/2024/12/04/voyage-code-3/

Alternatives

Alternatives

Embeddinghub

Embeddinghub

Featureform
Voyage AI

Voyage AI

MongoDB
voyage-4-large

voyage-4-large

Voyage AI
Codestral Embed

Codestral Embed

Mistral AI

Categories

Categories

Integrations

Amazon SageMaker
Cohere
Comet
Confluent
DSPy
Databricks
Dify
Dynamiq
GitHub Copilot
Google Cloud Marketplace
Google Cloud Platform
LangChain
Milvus
NVIDIA AI Data Platform
Parallel
Patronus AI
Qdrant
Snowflake
Tadata
Vespa

Integrations

Amazon SageMaker
Cohere
Comet
Confluent
DSPy
Databricks
Dify
Dynamiq
GitHub Copilot
Google Cloud Marketplace
Google Cloud Platform
LangChain
Milvus
NVIDIA AI Data Platform
Parallel
Patronus AI
Qdrant
Snowflake
Tadata
Vespa
Claim Weaviate and update features and information
Claim Weaviate and update features and information
Claim voyage-code-3 and update features and information
Claim voyage-code-3 and update features and information