Paragon is an integrations platform that fits into the modern SaaS tech stack. Paragon's node.js SDK can slot into your frontend. Paragon's workflow engine can be a part of your backend, processing data between your application and 3rd-party APIs.

This guide walks through industry standard technology choices for building a RAG application. From vector databases to response evaluation tools, we cover different options per function category and our recommendations for starting your RAG tech stack.

AI companies are aggressively investing in building integrations for their AI products, so they can ingest knowledge from their users' 3rd party apps and files, and give their AI agents access to automate tasks across the stack. This article dives into the use cases and why there is such strong sense of urgency right now.

Resources are re-usable API connections for your own internal services

3rd party webhooks are critical for enabling real-time integration use case. But because there are no standards, they can be very hard to build and maintain - we cover all the challenges to watch out for in this article.

Build custom triggers on top of any 3rd party webhook API in Paragon, for any integration.

Most AI SaaS companies today are implementing RAG with vector databases, but knowledge graphs are starting to pick up steam as the importance of retrieval accuracy becomes more apparent. We'll compare both options to help you better pick the right approach to use.

How do you reconcile permissions in a vector database within a RAG system when each 3rd party data source has their own permissions system? We explore the various approaches to implementing RAG with permissions in a multi-tenant environment.

Context is critical for LLMs, but it lives in unstructured data that's scattered across hundreds of your users' files and apps. But extracting that valuable context comes with many challenges, which we cover in this article.

Sharing some of the challenges that we had to overcome when building Paragon's workflow engine in order to support our customers' enterprise scale ingestion jobs.