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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

The newest version in the Llama series, Llama 3.3, represents a significant advancement in language models aimed at enhancing AI's capabilities in understanding and communication. It boasts improved contextual reasoning, superior language generation, and advanced fine-tuning features aimed at producing exceptionally accurate, human-like responses across a variety of uses. This iteration incorporates a more extensive training dataset, refined algorithms for deeper comprehension, and mitigated biases compared to earlier versions. Llama 3.3 stands out in applications including natural language understanding, creative writing, technical explanations, and multilingual interactions, making it a crucial asset for businesses, developers, and researchers alike. Additionally, its modular architecture facilitates customizable deployment in specific fields, ensuring it remains versatile and high-performing even in large-scale applications. With these enhancements, Llama 3.3 is poised to redefine the standards of AI language models.

Description

Progress Agentic RAG is a SaaS platform that enhances Retrieval-Augmented Generation by automatically indexing, searching, and producing AI-driven insights from both structured and unstructured business information, such as documents, emails, videos, and presentations. It achieves this by merging RAG with intelligent workflows that can reason, classify, summarize, and answer inquiries while providing traceable and verifiable outcomes, all without necessitating that users create or manage their own RAG infrastructure. This solution is modular and operates as a no-code RAG-as-a-Service, facilitating AI readiness for organizations by allowing them to extract contextual intelligence and business insights through natural language queries and output metrics focused on quality. Furthermore, it seamlessly integrates with any leading Large Language Model (LLM) and accommodates multilingual and multimodal content for indexing and retrieval. Noteworthy features include AI-driven summarization and classification, the generation of Q&A from enterprise data, and a Prompt Lab that enables the validation of LLM behavior through customized prompts. Additionally, the platform is designed to enhance user experience by simplifying complex tasks and ensuring that organizations can derive maximum value from their data effortlessly.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

AICamp Yes 
Agenta Yes 
Amazon S3 No 
Azure Marketplace Yes 
BlueFlame AI Yes 
Decopy AI Yes 
Evertune Yes 
Fleak Yes 
FriendliAI Yes 
Google Drive No 
Java Yes 
LM-Kit.NET Yes 
Meta AI Yes 
Okara Yes 
PostgresML Yes 
Requesty Yes 
SQL Yes 
Scala Yes 
SurePath AI Yes 
Waveloom Yes 

Integrations

AICamp No 
Agenta No 
Amazon S3 Yes 
Azure Marketplace No 
BlueFlame AI No 
Decopy AI No 
Evertune No 
Fleak No 
FriendliAI No 
Google Drive Yes 
Java No 
LM-Kit.NET No 
Meta AI No 
Okara No 
PostgresML No 
Requesty No 
SQL No 
Scala No 
SurePath AI No 
Waveloom No 

Pricing Details

Free
Open source
Free Trial No 
Free Version Yes 

Pricing Details

$700 per month
Free Trial Yes 
Free Version 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 

Deployment

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

Customer Support

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

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Types of Training

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

Types of Training

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

Vendor Details

Company Name

Meta

Founded

2004

Country

United States

Website

www.llama.com/docs/model-cards-and-prompt-formats/llama3_3/

Vendor Details

Company Name

Progress Software

Country

United States

Website

www.progress.com/agentic-rag

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