Retrieval-Augmented Generation 8
All-in-one backend-as-a-service for building AI-native applications and workflows.
Powabase is an all-in-one backend-as-a-service (BaaS) platform specifically designed for AI-native applications. It integrates a dedicated Postgres database with pgvector, an out-of-the-box Retrieval-Augmented Generation (RAG) pipeline, AI agent runtimes, and drag-and-drop visual workflows into a single system. The platform is optimized for modern AI coding agents like Claude Code, Codex, and Cursor, allowing software development agencies and in-house IT teams to ship AI products or add AI automation to existing infrastructure quickly and cost-effectively without managing fragmented services.
Universal, self-updating context layer for AI agents and LLMs via MCP.
Unabyss is a universal context layer and context management headquarters designed for AI tools, LLMs, and agents. It connects to the apps you use daily to automatically extract, structure, and update your personal or company context. Available via the Model Context Protocol (MCP), it acts as a single source of truth that securely syncs your data across various AI agents and development environments. It features granular permission control, allowing users to segment context and strictly manage what data each individual AI tool or agent is authorized to see.
Private LLM with RAG for secure Q&A and AI-powered search.
eLLMo is an exclusive Private LLM (Large Language Model) designed to protect client privacy. Enhanced with RAG (Retrieval-Augmented Generation), it answers questions on client data and documents, breaking silos within teams. It's an On-Prem deployed solution offering Enterprise Large Language Model Operations. eLLMo provides AI-powered search and generative insights, redefining information access with advanced AI capabilities. It leverages LLM-based Question and Answer (Q&A) models and a powerful Platform as a Service (PaaS) API with LLM vector search, excelling in generative AI search and fine-tuning for specific needs.
Open-source tool for building document question-answering systems with local AI models.
RLAMA (Retrieval-Augmented Local Assistant Model Agent) is an open-source AI solution that integrates with local AI models to create, manage, and interact with Retrieval-Augmented Generation (RAG) systems. It allows users to build powerful document question-answering systems with multiple document formats, advanced semantic chunking, and local storage and processing.
AI-powered knowledge management platform for organizing and accessing corporate knowledge.
Hakutaku is an AI-powered knowledge management platform designed to transform disorganized corporate knowledge into a structured, understandable, and useful resource. It connects data from various sources like Slack, Google Drive, and Notion to create a unified knowledge base. Using advanced Retrieval-Augmented Generation (RAG) technology, Hakutaku provides accurate answers to questions, understands context, and improves knowledge retention across an organization.
AI-powered tool for exploring and understanding research papers using natural language.
PaperLens is an AI-powered tool designed to help users explore and understand research papers. It allows users to search through millions of peer-reviewed papers using natural language queries and verify scientific claims with supporting evidence from arXiv, PubMed Central, and other leading academic databases. The platform combines cutting-edge AI technology with an intuitive design to streamline the research process.
Web crawler for LLM/RAG, reduces retrieval time.
HyperCrawl is a zero-latency web crawler specifically designed for retrieval-based LLM development and RAG applications. It aims to significantly reduce retrieval time in RAG systems by up to 95%. It's built for ML engineers to boost retrieval processes by eliminating the crawl time of domains, using advanced methods to create a novel, ML-first web crawler.
Cloud platform simplifying serverless RAG pipeline development and deployment.
SciPhi is a cloud platform for developers that simplifies building and deploying serverless RAG pipelines. Built on top of the open source R2R framework, it enables builders to focus on creating innovative applications rather than managing infra. SciPhi provides features like document ingestion, user management, advanced RAG, enterprise-grade RAG infrastructure, universal document processing, enterprise access control, and advanced document intelligence.
