Best Retrieval-Augmented Generation (RAG) Software for Google

Find and compare the best Retrieval-Augmented Generation (RAG) software for Google in 2026

Use the comparison tool below to compare the top Retrieval-Augmented Generation (RAG) software for Google on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.

  • 1
    Graphlogic GL Platform Reviews
    Graphlogic Conversational AI Platform consists of: Robotic Process Automation for Enterprises (RPA), Conversational AI, and Natural Language Understanding technology to create advanced chatbots and voicebots. It also includes Automatic Speech Recognition (ASR), Text-to-Speech solutions (TTS), and Retrieval Augmented Generation pipelines (RAGs) with Large Language Models. Key components: Conversational AI Platform - Natural Language understanding - Retrieval and augmented generation pipeline or RAG pipeline - Speech to Text Engine - Text-to-Speech Engine - Channels connectivity API Builder Visual Flow Builder Pro-active outreach conversations Conversational Analytics - Deploy anywhere (SaaS, Private Cloud, On-Premises). - Single-tenancy / multi-tenancy - Multiple language AI
  • 2
    Graphlit Reviews

    Graphlit

    Graphlit

    $49 per month
    Whether you're developing an AI assistant, chatbot, or improving your current application with LLMs, Graphlit simplifies the process. It operates on a serverless, cloud-native architecture that streamlines intricate data workflows, encompassing data ingestion, knowledge extraction, LLM interactions, semantic searches, alert notifications, and webhook integrations. With Graphlit's workflow-as-code methodology, you can systematically outline every phase of the content workflow. This includes everything from data ingestion to metadata indexing and data preparation, as well as from data sanitization to entity extraction and data enrichment. Ultimately, it facilitates seamless integration with your applications through event-driven webhooks and API connections, making the entire process more efficient and user-friendly. This flexibility ensures that developers can tailor workflows to meet specific needs without unnecessary complexity.
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB