【Introducing Chat Hub】
If you’ve been following the rise of AI in the workplace, you know the challenge: AI usage is becoming commonplace, but it’s often unmanaged. Chat Hub changes that by providing a single, unified interface for your organization to direct users for all AI-related tasks and processes,
【Introducing Custom Project Roles and User Provisioning via SSO, built for Enterprise governance】
Projects sit at the heart of how n8n scales inside larger organizations. They are the unit that allows a single n8n instance to be shared safely across teams, business units, and environments, without turning automation into a free-for-all.
Each Project acts as an isolated workspace with its own workflows, credentials,
【Human in the loop automation: Build AI workflows that keep humans in control】
Learn how human-in-the-loop automation combines AI efficiency with human oversight. Build smarter workflows with checkpoints using n8n.
【Announcing Autosave & More!】
We're introducing a safer and more reliable way to manage your workflow development lifecycle with the arrival of Autosave, Versioned Publishing, and Concurrency Protection.
【AI Workflow Builder Best Practices】
We recently released AI Workflow Builder for Starter, Pro and Enterprise Cloud customers, turning your natural language prompts into working automations.
Instead of launching into building a new workflow from scratch with a blank canvas, you can easily get your automation ideas out of your head and into a functioning
【15 best n8n practices for deploying AI agents in production】
This guide walks you through the 15 best n8n practices for deploying production-ready AI Agents. Choose the best infrastructure, scale queue mode, handle errors, monitor, and deploy AI Agents reliably in n8n.
https://blog.n8n.io/best-practices-for-deploying-ai-agents-in-production/
【Security Advisory: Security Vulnerability in n8n Versions 1.65-1.120.4】
Security update: Upgrade recommended for users on versions below 1.20.4
【Multi-agent systems: Frameworks & step-by-step tutorial】
Discover multi-agent AI patterns, communication, costs, risks, and real-world use cases. Compare visual builders like n8n with code-first SDKs.
【A practical guide to building your RAG pipeline in n8n】
Explore how to build a full RAG pipeline in n8n without heavy frameworks. Compare code-first approaches to visual workflows for faster iteration and easier maintenance.
【Building your own LLM evaluation framework with n8n】
In this hands-on tutorial, we'll guide you through creating a low-code LLM evaluation framework using n8n. Learn key concepts like “LLM-as-a-Judge” and build a custom evaluation path that ensures you can deploy updates, test new models, and maintain quality with total confidence.
【Introducing n8n 2.0】
n8n 2.0 focuses on secure-by-default execution with better reliability and performance.
【The 9 best AI workflow automation tools in 2026】
Looking for AI workflow automation tools? Compare n8n, Zapier, Make, and 6 other top platforms. Find the best fit for beginners, developers, and enterprise teams.
【Build a fast, deep research automation flow with Oxylabs and n8n】
Learn about web scraping and how to to build an automated web intelligence workflow.
https://blog.n8n.io/build-a-fast-deep-research-automation-flow-with-oxylabs-and-n8n/
【n8n Expands What’s Possible in Enterprise Automation with Microsoft Agent 365】
A new integration with Microsoft Agent 365 lets teams build agentic systems that connect n8n’s AI orchestration layer and automation ecosystem with Microsoft’s productivity suite.
https://blog.n8n.io/n8n-expands-whats-possible-in-enterprise-automation-with-microsoft-agent-365/
【AI Agent Orchestration Frameworks: Which One Works Best for You?】
Discover AI agent orchestration frameworks like n8n, LangGraph, CrewAI that power scalable, multi-agent AI orchestration in 2025.
【Implementing Rerankers in Your AI Workflows】
Boost your RAG pipeline’s accuracy with rerankers that reorder results by true semantic relevance—deliver smarter, faster, and more precise AI search!
https://blog.n8n.io/implementing-rerankers-in-your-ai-workflows/
【n8n raises $180m to get AI closer to value with orchestration】
We just raised $180 million in Series C funding, bringing our total funding to $240 million and our valuation to $2.5 billion.
The round is led by Accel, with support from Meritech, Redpoint, Evantic and Visionaries Club. Corporate investors NVentures (NVIDIA’s venture capital arm) and T.Capital
【The n8n Scalability Benchmark】
Ever wondered just how hard you can push n8n before it starts waving the white flag? We pushed n8n to the limits, with impressive results.
When you’re running mission-critical workflows, you need to know your limits. So we recently put different n8n deployments through their paces –
【Agentic RAG: A Guide to Building Autonomous AI Systems】
Standard RAG is accurate but inflexible. Agentic RAG is the upgrade, using smart AI agents in dynamic workflows. These agents choose the right tool for any query, like a database or web search, and verify their own answers. This guide explains what Agentic RAG is and shows you practical examples.
【Practical Evaluation Methods for Enterprise-Ready LLMs】
Discover practical evaluation methods for enterprise-ready LLMs. Learn how to measure accuracy, safety, and reliability—and see how n8n’s built-in evaluation tools make it easy to test and improve AI workflows.
https://blog.n8n.io/practical-evaluation-methods-for-enterprise-ready-llms/
【12 Best Autonomous AI Agents – 2025’s Top Picks】
Tired of doing repetitive tasks? These 12 AI agents handle complex workflows independently while you focus on the fun stuff. Plus n8n tutorials for ultimate customization!
【Evaluating RAG, aka Optimizing the Optimization】
RAG isn’t foolproof. Explore common hallucinations, evaluation metrics, and how to improve RAG accuracy in n8n.
https://blog.n8n.io/evaluating-rag-aka-optimizing-the-optimization/
【New plan, no active workflow limits — n8n's new pricing explained.】
If you’ve been around n8n for a while, you know we like sharing openly what we’re working on and involving our community along the way. So, when we decided to review our pricing earlier this year, we followed that same approach.
We spent months talking with
https://blog.n8n.io/build-without-limits-everything-you-need-to-know-about-n8ns-new-pricing/
【n8n execution advantage: An overview of our unique pricing model】
n8n offers a pricing model designed to make automation accessible and scalable for everyone. Unlike other platforms that charge per operation, step, or task, n8n charges based on full workflow executions. This means your costs grow only when your automations run from start to finish and deliver value, not when
【Beyond the Hype: 10 Best AI Agents That Truly Work】
This guide explores five powerful types of AI agents gaining traction in 2025—and how platforms like n8n make it easier than ever to build or integrate them.
Ready to find out which AI agents are worth your attention? Let’s dive in.
【What Is AI Sentiment Analysis and How to Build It with n8n?】
Learn how to use AI sentiment analysis in n8n to intelligently automate workflows. Explore sentiment types, real-world use cases, and step-by-step guidance to build an agent-based system that classifies and explains email intent.
【7 Best AI Agent Builders: An Expert Market Breakdown】
Explore 7 top AI agent builders: workflow-native, AI-native & hybrid. Compare AI agent builder platforms by use case, integration & flexibility!
【MCP will be the death of low-code automation, and other spooky stories】
Explore the state and future of MCP in AI agents—from vendor security and model risks to cost and orchestration. MCP shows promise but faces adoption hurdles due to immaturity, security flaws, and backward compatibility challenges.
https://blog.n8n.io/mcp-will-be-the-death-of-low-code-automation-and-other-spooky-stories/
【Introducing Evaluations for AI workflows】
Distilling the complexity of AI Evaluations frameworks into a practical paradigm
https://blog.n8n.io/introducing-evaluations-for-ai-workflows/
【A Breakdown of the AI Agent Development Tool Market】
So much of LLM volatility and unpredictability can be solved by defining deterministic logic around LLM outputs.
This is the premise of the enterprise AI Agent development tools report that I wrote for n8n, which explored the market of no-code/low-code automation tools with AI implementations. Agents depend on
https://blog.n8n.io/a-breakdown-of-the-ai-agent-development-tool-market/
【Community nodes available on n8n Cloud】
Starting with a select group of verified nodes, users can install community and partner-built integrations directly from the canvas. This launch marks the next step in expanding our trusted ecosystem, powered by community contributions and vendor collaborations.