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What is eRAG?

GigaSpaces eRAG (Enterprise Retrieval Augmented Generation) is an AI-centric platform designed to enhance decision-making within businesses by enabling natural language communication with structured data sources like relational databases. Unlike traditional generative AI models that can often yield unreliable or fabricated outputs when dealing with structured data, eRAG employs deep semantic reasoning to transform user questions into SQL queries, retrieve relevant data, and produce accurate, context-aware responses. This pioneering approach ensures that the information provided is drawn from real-time, dependable data, thereby mitigating the risks associated with unverified outputs from AI systems. In addition, eRAG seamlessly integrates with diverse data sources, allowing organizations to fully leverage their existing data infrastructure. Beyond its integration capabilities, eRAG features comprehensive governance tools that monitor user interactions to maintain compliance with regulatory standards, thus encouraging responsible use of AI technology. This multifaceted strategy not only improves decision-making but also strengthens data integrity and regulatory compliance throughout the organization. As a result, organizations can trust that their AI-driven insights are both accurate and aligned with best practices in data management.

What is Cohere Embed?

Cohere's Embed emerges as a leading multimodal embedding solution that adeptly transforms text, images, or a combination of the two into superior vector representations. These vector embeddings are designed for a multitude of uses, including semantic search, retrieval-augmented generation, classification, clustering, and autonomous AI applications. The latest iteration, embed-v4.0, enhances functionality by enabling the processing of mixed-modality inputs, allowing users to generate a cohesive embedding that incorporates both text and images. It includes Matryoshka embeddings that can be customized in dimensions of 256, 512, 1024, or 1536, giving users the ability to fine-tune performance in relation to resource consumption. With a context length that supports up to 128,000 tokens, embed-v4.0 is particularly effective at managing large documents and complex data formats. Additionally, it accommodates various compressed embedding types such as float, int8, uint8, binary, and ubinary, which aid in efficient storage solutions and quick retrieval in vector databases. Its multilingual support spans over 100 languages, making it an incredibly versatile tool for global applications. As a result, users can utilize this platform to efficiently manage a wide array of datasets, all while upholding high performance standards. This versatility ensures that it remains relevant in a rapidly evolving technological landscape.

Media

Media

Integrations Supported

Amazon RDS
Cohere
GigaSpaces
Google Cloud BigQuery
IBM Db2
Oracle Database
PostgreSQL
SAP Cloud Platform
SQL
SQL Server

Integrations Supported

Amazon RDS
Cohere
GigaSpaces
Google Cloud BigQuery
IBM Db2
Oracle Database
PostgreSQL
SAP Cloud Platform
SQL
SQL Server

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$0.47 per image
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

GigaSpaces

Date Founded

2000

Company Location

Israel

Company Website

www.gigaspaces.com/products/erag

Company Facts

Organization Name

Cohere

Date Founded

2019

Company Location

Canada

Company Website

cohere.com/embed

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