Retrieval-Augmented Generation (RAG) applications depend on efficient data ingestion, transformation, and storage to deliver relevant responses quickly. However, managing the preprocessing pipeline and integrating a high-performance vector database can be complex and resource-intensive.

To simplify this process, Unstructured Platform now offers seamless Redis Cloud integration. By combining Unstructured’s advanced data preprocessing capabilities with Redis Cloud’s in-memory performance, data teams can build RAG applications that are both scalable and lightning-fast. This integration enables you to process unstructured data and store it efficiently in Redis Cloud, unlocking high-speed vector search and retrieval capabilities.

Why Redis?

Redis is a great choice for RAG applications because of its speed, scalability, and ability to be used for many real-time use cases. It provides several key features that enhance vector search and retrieval:

• Vector Indexing: Stores and organizes vector embeddings efficiently, enabling rapid similarity searches.
• Semantic Caching: Improves response times and reduces processing costs by storing frequently accessed results, such as commonly asked questions in a knowledge retrieval system.
• LLM Context Management: Maintains conversation history for AI-driven interactions, ensuring continuity and better contextual understanding in chatbot or virtual assistant applications.
• High Performance: With its in-memory architecture, Redis delivers low-latency, high-throughput operations, making it an excellent choice for large-scale AI and RAG workloads.
• Broad integrations: Redis works with the top GenAI tools and frameworks including Unstructured so you can focus on building apps instead of maintaining infrastructure.

Unstructured Platform + Redis

With the Unstructured Platform’s Redis Cloud integration, data teams can:

• Process unstructured data from 60+ file formats using Unstructured’s robust parsing tools
• Convert documents into structured, AI-ready chunks with intelligent partitioning
• Store document content and metadata directly in Redis Cloud for fast retrieval
• Utilize Redis Cloud’s vector search capabilities for efficient similarity matching
• Scale seamlessly with high-throughput, batch-processing support

By leveraging Redis Cloud’s real-time processing capabilities alongside Unstructured’s powerful data transformation tools, engineers can build high-performance RAG applications that deliver faster, more accurate responses. Whether handling live data streams or extensive document repositories, this integration optimizes retrieval speed and efficiency, reducing complexity in AI-driven workflows.

Setting Up the Integration

Here's how to configure the Redis Cloud integration in Unstructured Platform:

Using the Platform UI

1. Navigate to the Connectors section in the sidebar and click Destinations
2. Click "New" and provide a unique name for your connector
3. Choose "Redis" as the Provider and fill out the following configuration details:

• Connection URI, or hostname/port/username/password
• Database index (typically 0-15)
• SSL settings (if applicable)
• Batch size for uploads

Screenshots of a sample Redis Cloud destination connector configuration:

Using the Platform API

For those who prefer programmatic setup, here's how to create a Redis Cloud destination connector using our API:

Get started!

If you're already an Unstructured Platform user, the Redis Cloud integration is available in your dashboard today!

Expert access

Need a tailored setup for your specific use case? Our engineering team is available to help optimize your implementation. Book a consultation session to discuss your requirements here.