DeeperML

Several companies are pushing advancements in Retrieval Augmented Generation (RAG) technology, aiming to enhance AI capabilities. Contextual AI is focusing on developing specialized RAG agents designed for expert knowledge work, enabling more accurate and efficient AI solutions for specific domains. These agents are engineered for high-value, domain-specific knowledge tasks, representing a significant step beyond general-purpose RAG. Contextual AI has also launched a platform with features to build, evaluate, and deploy these RAG agents.

Ragie has unveiled new tools including Ragie Connect, which simplifies the integration of RAG pipelines into SaaS applications, allowing developers to easily embed RAG into their applications by connecting user data with minimal code. Ragie also announced Advanced Retrieval Mode and Base Chat. Advanced Retrieval Mode is designed to enhance retrieval accuracy using hybrid search and recency bias to prioritize current data. Ragie Base Chat is an open-source, multi-tenant chatbot, allowing companies to interact with their data from various sources like Google Drive and Salesforce, acting as a self-hosted solution to chat with their data.


References :

• aithority.com: Ragie Launch Week: Game-Changing RAG Tooling for Developers
• techstrong.ai: Contextual AI Specialized Agents, Even More Raggy than RAG
• www.marktechpost.com: Chat with Your Documents Using Retrieval-Augmented Generation (RAG)
• MarkTechPost: Chat with Your Documents Using Retrieval-Augmented Generation (RAG)

Classification:

• HashTags: #RAG #AItools #AIWorkflow
• Target: AI Developers
• Product: RAG Applications
• Feature: RAG Tooling and Custom Agents
• Type: AI
• Severity: Informative