Existing integration platforms are not going to make it in the post-AI world. That’s why we’re unveiling Paragon 2.0—one integration platform with three purpose-built products that will fundamentally shape how developers build integrations moving forward.

“The first thing you need to consider when you’re a pm is to define what kind of trust you need to build with your users”. In our latest episode of Future Proof, we sat down with Laura Burkhauser, VP of Product at @DescriptApp (yes, the same tool we used to edit this episode).

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🚀 Introducing Managed Sync: 3rd-party ingestion & access control for RAG. Building AI products that deliver real value means giving LLMs access to your users' internal data and knowledge sources. But ingesting data from dozens of 3rd-party APIs while maintaining proper access.

“So you are actually seeing a movement away from just one tiny niche and then, a lot more expansion from a lot of different players in more general purpose, enterprise productivity”. - @RichardSocher , CEO and Cofounder of If you haven’t seen it yet,

“ If you want to make LLMs accurate, up to date or have citations, you need to have a very strong search backend both over external data on the web as well as private data on your own internal company context.” - @RichardSocher , CEO and Cofounder of

“Always assume the baseline model gets better and better, but data is ultimately always a great moat…”. In this episode of Future Proof: Building AI Products that last, we chat with CEO and co-founder, @RichardSocher , on how to build a platform that can

In this tutorial, we discuss how to add agentic capabilities into your AI application, allowing your RAG application to not only read data from third parties but also write data (take action) to those third-party apps as well.

“Your system will only be as good as the quality of the access controls beneath it”. In this episode of Future Proof: Building AI Products that last, we chat with @levie, CEO and Cofounder of @Box, on what it takes to build successful Enterprise AI products. We cover:.- Why

We built an AI agent that can access Slack messages and analyze them to curate the perfect Spotify playlist. Build any 3rd-party automation you want with the Paragon MCP. Get access yourself at

With the Paragon MCP server, we built an AI agent that automatically updates tasks in Asana. Take a look, and try yourself at

Building an AI app, that connects and pulls from your users’ CRMs isn’t a challenge anymore. Watch how we built an AI agent that authenticates and connects to Salesforce and HubSpot, pulls in data and publishes to a Google Sheets, all in a mater of minutes. We used Paragon’s MCP

Looking for an MCP server with OAuth capabilities. Get fully managed authentication into 100 different SaaS apps through Paragon's MCP. Watch as our AI agent authenticates into Gmail, searches for messages, and automatically finds the time for a meeting. Connect to the MCP

Curious how companies like Copy ai and Unify GTM shipped their workflow builders? In this tutorial, learn how to easily create a workflow builder using xyflow and Paragon’s ActionKit API. Construct drag-and-drop workflow interfaces with the ability to power over 1,000 third-party

Looking for an MCP that can authenticate multiple users? Watch how Paragon’s MCP powers any client to authenticate into GitHub and produce issue tickets within seconds. Curious? Try it for yourself

We got an AI Agent to authenticate into Google Drive and then make an ASCII art in Google Sheets, all with just one MCP. Watch our Developer Advocate walk you through it. If you want to connect your AI product to hundreds of 3rd-party tools, check out.

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

Another API change getting in the way of your integration development? The cost of maintaining integrations is very hard to estimate, with third-party API changes, issues with authentication, and much more. Offload these worries to Paragon, and enjoy your weekends again.

We built an AI knowledge chatbot that has context on all the information from a user's Slack messages, Google Drive files and Notion documents using create-llama, Pinecone, and Paragon. Check it out!

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