Nuclia + Pinecone
The ultimate RAG-as-a-Service solution

Why combine Nuclia RAG and Pinecone?
Nuclia RAG-as-a-Service now seamlessly integrates with Pinecone, offering a robust solution for organizations to index and retrieve vast amounts of data efficiently. This powerful combination provides you with the tools to turn your unstructured data into actionable insights.
Automatic indexing for maximum efficiency
Optimized for large datasets with Pinecone
When you create a knowledge box in Nuclia, you can choose to store the index in Pinecone. This is particularly beneficial for handling large datasets where full-text search is not critical during the retrieval phase. Pinecone’s vector search technology allows you to retrieve data quickly and efficiently, making it ideal for applications that require real-time processing.
Tailored solutions for every use case
Nuclia’s modular RAG platform is designed with flexibility in mind. You can customize your RAG pipeline to meet your unique requirements—whether it’s defining specific retrieval and chunking strategies or selecting the right embedding models.
This adaptability allows you to create solutions that fit your specific operational needs, ensuring that your AI applications are always aligned with your business goals.
Speed
Scalability
Flexibility
Make your data AI ready with Nuclia and Pinecone and get:
Nuclia prepares your unstructured data for AI and provides a diverse set of AI capabilities right out of the box. This allows you to concentrate on crafting your own AI product and delivering value, rather than investing time in developing capabilities
-> RAG-as-a-Service (Retrieval Augmeneted Generation as a Service)
-> AI Search and Generative Answers for unstrucutred data
-> AI auto classification
-> AI Summarization for your files
-> Multiple LLMs in just a click
-> Personalised user prompts definition
-> Named Entity detection & Knowledge Graph
-> AI Search Copilot
-> Generated Q&A
-> Synthetic questions generation
-> Continuous training and model adapters
-> Prompt Lab for LLM validation
Want to know more?
If you want to lear more and how we can help you to implement this, please use this form or join our community on Slack Community for technical support.
See you soon!