Overview
Ragie was a fully managed retrieval-augmented generation platform that enabled developers to connect documents and data to AI applications. It provided real-time indexing, agentic retrieval, multimodal support, and MCP tools. Note: Ragie was acquired by Ticketmaster in July 2025 and the platform has been shut down.
Our take
Ragie was a managed retrieval-augmented-generation service and shut down in July 2025. The listing stays so that anyone searching for it gets a clear answer. Its closure is a useful data point about this layer of the stack: managed RAG services have struggled commercially as the major model providers and databases absorbed the functionality.
Worth it if
Confirming the shutdown if you encountered a reference to it.
Look elsewhere if
Building anything — the service no longer exists.
✨ Features
Document Processing
Indexed and processed millions of documents for AI retrieval.
Agentic Retrieval
Context-aware retrieval that understood queries and returned relevant results.
MCP Integration
Model Context Protocol support for connecting RAG to AI agents.
Developer SDKs
Simple APIs and SDKs for integrating retrieval into applications.
⚖️ Pros & Cons
Pros
Cons
Categories
❓ Frequently Asked Questions
What should I use for retrieval now?
Most teams use the vector capability in a database they already run, which is simpler to operate than adding a dedicated service. Below roughly a hundred thousand documents that is usually sufficient. The infrastructure and database categories here list current options if you need something more specialised.
Why did managed RAG services struggle?
Because the layer got absorbed. Model providers added retrieval features, databases added vector support, and frameworks made assembling a pipeline straightforward — leaving a narrow band where a separate managed service was worth a separate vendor. It is a reasonable caution about building on any thin layer of someone else's stack.