Paragon

All the benefits of Embedded iPaaS, in code. We’re thrilled to announce the launch of Paragraph - a TypeScript framework purpose-built for authoring native integrations. Engineering teams can finally leverage all the features of Paragon such as a fully managed authentication, 3rd party API abstractions, and a serverless infrastructure, in an environment that they're familiar with —code. As a byproduct, this unlocks all the benefits of building in code, such as: - Version control - Code review - Collaboration - Code re-use Learn more about Paragraph in the link below! (You’ll also find a demo video made by our Lead PM, Ethan Lee)

Are you building RAG for your AI SaaS app? Your product must be able to ingest and retrieve your customers’ external knowledge. We’re excited to announce our upcoming webinar, External Data and Permissions Strategies for RAG. Join Jack Mu, Paragon Developer Advocate, as he walks through: - How to ingest all of your users’ external data, both existing data and new data - Chunking strategies to optimize for retrieval accuracy - How to model and reconcile third-party data permissions in your app Secure your spot now (link can be found in the comments below)

Congrats to 11x on the $50M Series B led by Andreessen Horowitz! We're excited to be the layer that will enable their AI digital workers to execute on the fully autonomous revenue workflows that span across the sales stack. They have an exciting roadmap ahead with a suite of new AI sales agents, so be on the lookout for their updates!

Excited to be at Lenny Rachitsky’s first summit! If you’re attending, come say hi!

Give your AI application agentic capabilities across 3rd party apps. Building on our AI chatbot series, this new tutorial shows you how to build an AI assistant that doesn't just read data, but can take action. It walks through adding write capabilities to your RAG application using LlamaIndex’s function tools to orchestrate and route actions, and Paragon for building the actual actions, including: Send Slack messages Create Salesforce contacts Chain together read and write operations seamlessly Link can be found in the comments, read now!

When building an AI RAG application, how do you handle permissions for 3rd party integration data at scale, across multiple integrations AND multiple types of integrations (file storage, CRMs, etc.)? We prioritized safety above all else in our last permissions tutorial for demonstrative purposes, but in production, considerations including schema unification and latency come into play. To address these production-level challenges, read our latest tutorial: Scaling 3rd Party Permissions and Access Control in RAG Tutorial: https://lnkd.in/ga96nE9r Repo: https://lnkd.in/gdgCUPvM

See how Frame built Universal Search and context-aware AI Employees into their product, using Paragon as the backbone for their integration infrastructure! We sat down with Nicolas, Frame's CEO, and Max, their VP of Engineering, to learn more about the integrations they built with Paragon and the experience using our platform. Read or watch the full customer story here --> https://lnkd.in/gWxkwcTR

The G2 Fall reports are here,?and Paragon was named a leader in the Embedded Integrations Platform category! Our product continues to evolve, supporting engineering teams to build reliable and scalable integrations for their products, 7x faster. We're now working with companies building RAG AI applications, and large-scale enterprises looking to connect all their customers’ data sources. A lot more updates are coming, so give us a follow if you haven't already!

Check out how you can build an enterprise knowledge AI application in just a few days with this tutorial!

Ensure your RAG-based AI application respects users' 3rd party data permissions. This tutorial shows how to build a permissions system that ensures your RAG application only retrieves context the querying user has access to (ie. your app shouldn't be able to retrieve a CEO’s 1:1 notes when answering questions from an intern). We used Pinecone as our vector store, Okta FGA as our permissions graph, LlamaIndex's create-llama as the base of our chatbot, and Paragon for the ingestion jobs to pull files and permissions from Google Drive and Dropbox. Tutorial: https://lnkd.in/g4yJEBNv Repo: https://lnkd.in/gN4kUeZZ