RAG Tools & Platforms

Turns documents and past sessions into a graph-plus-vector memory that AI agents can query across runs.

Best for: Developers building agents that need recall across sessions

Open-source search engine with vector storage and hybrid keyword-plus-semantic retrieval, self-hosted or run as a cloud service

Best for: Teams that want keyword and semantic retrieval from one index instead of two systems

Hosted platform for building and deploying AI agents

Best for: Agencies shipping support or sales bots for multiple clients

Knowledge graph from Munich that links scattered enterprise data so engineers and models can query it with sources attached.

Best for: Aerospace, rail, and manufacturing engineering teams

Open-source visual builder for LLM agents and RAG flows, deployable as an HTTP API or an MCP server.

Best for: teams prototyping RAG and agent flows visually before coding them

Agent-building platform with a playground, visual workflow builder, agent marketplace and bring-your-own-model support, on web and mobile.

Best for: Development teams wanting a managed layer for building AI agents

Postgres backend bundled with a RAG pipeline, agent runtime and a visual workflow builder

Best for: Teams rebuilding the same Postgres plus RAG plus agent stack on every project

Open-source vector search engine written in Rust, available self-hosted or as a managed cloud for RAG and recommendation apps.

Best for: Teams building RAG or semantic search who want an open-source, self-hostable store

No-code platform for building and governing enterprise AI agents, sold through sales

Best for: Publishers and education companies with content-processing backlogs

Open-source search and vector engine that combines text, vectors, ranking and model inference for RAG, recommendations and agents.

Best for: Teams building large-scale search, recommendation or RAG systems that need hybrid ranking

Answers support tickets from your own historical ticket data

Best for: Ecommerce and SaaS support teams with thousands of resolved tickets and repetitive queries

Builds retrieval chatbots from company documents, sites and helpdesk content

Best for: Support teams turning an existing help centre into a self-serve answer bot

A serverless platform for building, deploying, and monitoring AI agents across 600-plus LLMs.

Best for: developers who want model routing, RAG, and workflows in one platform

Documentation service and MCP server that feeds version-specific library docs and code examples into AI coding assistants.

Best for: Developers using AI editors with frameworks that change often, such as Next.js or Supabase

Low-code builder for forkable AI workflows deployed to WhatsApp, SMS, voice lines, Slack and web widgets

Best for: NGOs and gov-tech teams shipping multilingual WhatsApp or IVR assistants

Turns your docs, tickets and wikis into a question-answering agent that cites its sources and answers inside Slack, Jira or Zendesk.

Best for: internal IT or HR helpdesks with a large document corpus

Open-source data framework for retrieval and agents, with LlamaParse as the paid document parsing, extraction and indexing service

Best for: Developers building retrieval-augmented answers over PDFs, contracts and reports with tables and scans

Managed MongoDB cloud database with built-in vector search, hybrid search and Voyage AI embeddings for RAG and agent apps.

Best for: Teams already on MongoDB adding RAG or semantic search

Source-available multimodal retrieval engine that embeds whole document pages, so RAG works over diagrams and datasheets.

Best for: Engineering and manufacturing teams searching technical manuals and datasheets

Managed vector database for similarity search over billions of embeddings, with serverless and BYOC options

Best for: RAG and agent memory backends that need low-latency retrieval at scale

Paid Node boilerplate for AI SaaS: auth, Stripe or Lemon Squeezy billing, RAG endpoints and demo apps

Best for: Solo developers shipping a first AI SaaS quickly

Private on-device AI assistant for chatting with your documents, running agents and transcribing meetings, free on desktop.

Best for: Privacy-conscious users who want chat with their documents without sending files to a cloud

Open-source canvas for building LLM workflows, agents and RAG pipelines, hosted or self-run

Best for: Teams that want to self-host an agent and RAG builder without writing the orchestration layer

Trains a support chatbot on your docs and help center, then embeds it on the site or in Slack

Best for: Support teams with existing documentation they want to make answerable

No-code agent-as-a-service platform that builds RAG-backed AI agents on your own documents, in the cloud or on-premise.

Best for: Teams building internal or customer-facing agents on private documents without an ML team

Paste your URL, it crawls the site and puts a conversion-focused chat agent on your pages.

Best for: single marketing sites that want a pre-sales chat agent

Apache-licensed Python framework for building RAG pipelines and agents out of swappable components, maintained by deepset.

Best for: Python teams building production RAG or search applications

MIT-licensed Python/JavaScript framework for building LLM agents, with 1,000+ model and tool integrations

Best for: Teams prototyping agents quickly against many models and tools

Open-source AI chat and search layer that connects any LLM to a company's apps, with permission-aware retrieval and self-hosting.

Best for: IT teams that must keep documents and embeddings inside their own network

AI search engine that answers questions with cited sources instead of a list of links.

Best for: People who want a direct answer with sources instead of scanning search results

Turns PDFs, scans, slides, emails and other messy files into clean structured data for RAG and LLM pipelines.

Best for: Developers preparing mixed document collections for RAG or fine-tuning

Open-source web app for asking questions about an uploaded PDF, built on Together AI and vector search.

Best for: Occasional PDF Q&A without paying for a subscription

Open-source Python toolkit that scores RAG and agent apps with LLM-based metrics and generates synthetic test sets.

Best for: Engineers measuring retrieval and answer quality of a RAG pipeline before release

Alani, a persistent agent that answers with citations over your files, a shared community library and business systems.

Best for: researchers keeping a cited personal library across mixed media