Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Description

Gemini Embedding models, which include the advanced Gemini Embedding 2, are integral to Google's Gemini AI framework and are specifically created to translate text, phrases, sentences, and code into numerical vector forms that encapsulate their semantic significance. In contrast to generative models that create new content, these embedding models convert input into dense vectors that mathematically represent meaning, facilitating the comparison and analysis of information based on conceptual relationships instead of precise wording. This functionality allows for various applications, including semantic search, recommendation systems, document retrieval, clustering, classification, and retrieval-augmented generation processes. Additionally, the model accommodates input in over 100 languages and can handle requests of up to 2048 tokens, enabling it to effectively embed longer texts or code while preserving a deep contextual understanding. Ultimately, the versatility and capability of the Gemini Embedding models play a crucial role in enhancing the efficacy of AI-driven tasks across diverse fields.

Description

Weaviate is an open-source vector database built for the AI era, giving teams one platform for vector search, retrieval-augmented generation, and agent memory. Store data objects together with embeddings from your preferred machine learning models and scale effortlessly to billions of objects. Import your own vectors or rely on Weaviate's built-in vectorization, then search across vector, keyword, and hybrid methods to get highly relevant results, even when filters are applied. By connecting to today's leading large language models, Weaviate helps you build grounded search and question-answering over your own data. The platform reaches well beyond storage: its Query Agent translates plain-language questions into accurate queries with citations, Engram delivers managed long-term memory for AI agents, and Weaviate Embeddings removes the work of running your own embedding pipeline. Available as self-hosted open source or fully managed Weaviate Cloud across AWS, GCP, and Azure, backed by SOC 2 Type II, native multi-tenancy, replication, and role-based access control. From semantic search to recommendation to fully agentic applications, Weaviate is the foundation to ship AI products faster.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Anthropic No 
Azure Marketplace No 
Cleanlab No 
Cohere No 
Cursor No 
DSPy No 
Dynamiq No 
Firecrawl No 
Gemini CLI No 
Gemini Enterprise Yes 
Google AI Studio Yes 
Google Cloud Marketplace No 
Hugging Face No 
IBM API Connect No 
LlamaIndex No 
Mem0 No 
Mistral AI No 
Patronus AI No 
Semantic Kernel No 
Snowflake No 

Integrations

Anthropic Yes 
Azure Marketplace Yes 
Cleanlab Yes 
Cohere Yes 
Cursor Yes 
DSPy Yes 
Dynamiq Yes 
Firecrawl Yes 
Gemini CLI Yes 
Gemini Enterprise No 
Google AI Studio No 
Google Cloud Marketplace Yes 
Hugging Face Yes 
IBM API Connect Yes 
LlamaIndex Yes 
Mem0 Yes 
Mistral AI Yes 
Patronus AI Yes 
Semantic Kernel Yes 
Snowflake Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Free
Open source (free); free Weaviate Cloud tier; paid Cloud plans from $45/mo.
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Google

Founded

1998

Country

United States

Website

blog.google/innovation-and-ai/models-and-research/gemini-models/gemini-embedding-2/

Vendor Details

Company Name

Weaviate

Founded

2019

Country

The Netherlands

Website

weaviate.io

Product Features

Alternatives

Alternatives

Embeddinghub Reviews

Embeddinghub

Featureform