Learn the fundamentals of AI agent tool calling and how it can enable your AI product to automate tasks across your users' workflows.

One API to give your AI agent 1000+ integration tools.

Everyone is racing to ingest data for RAG - but it isn't always optimal for accurate/efficient retrieval. Learn when you should leverage API-based query-time retrieval instead.

Building AI products? This comprehensive guide covers everything you need to know about retrieval augmented generation (RAG).

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.