Agentic Business Orchestration Beta

You are invited to join the weekly Agent and Orchestration Office Hours session focused on learning how to design, build, and operationalize AI agents.When? Weekly - Tuesdays 3:00 PM CT (Americas) / Wednesdays 8:00 AM AEDT (APAC)Where? Teams call: Join here!Each session will walk through a specific topic with a short demo and practical guidance you can apply immediately, such as:Build AI agents and understand when to use agents vs. simple actions Embed agents into workflows and orchestrations Design multi-agent solutions and master agents Connect agents to knowledge sources, tools, and external systems Implement guardrails, testing strategies, and human-in-the-loop patterns Deploy agents safely and monitor performance in production

Hi everyone! 👋If you've been hearing the word "Orchestration" floating around lately, today's the day. We're opening it up to all customers, and I wanted to give you a proper walkthrough before you dive in. So, what problem does it solve?Here's the honest truth about a lot of business processes: they don't behave the way flowcharts suggest they will.You build a workflow for employee onboarding, a customer claim, or a vendor approval. It works great, right up until reality intervenes. The case needs to go back a step. A new event changes the context. Two teams need to be working on different parts simultaneously.Before long, you're adding branches on branches, or spinning up a separate workflow to handle an exception that probably wasn't that exceptional.Orchestration is built for exactly this kind of process, and it's grounded in a case management approach. 

As you start building your Nintex AI agents, the first step is knowing where to configure and manage them. All agent setup happens in Nintex Agent Designer, a dedicated experience where you define how your agent thinks, behaves, and interacts with tools and data.  For more details and instructions use any of the following resources:Nintex HelpConfigure an Agent blog  (by Andy Hayes)

AI is on everyone’s radar; the question is knowing where to start? The good news, you don’t need a massive overhaul to begin benefiting from AI. In fact, most companies find success by identifying just one clear use case and running a small instance or project. This introductory blog post – the first in our series on building AI agents for business applications – lays out practical best practices for getting started. We’ll explore why it’s smart to start with small, simple projects (think five steps or fewer), how to focus on straightforward, deterministic tasks for quick wins, and which high-impact, low-complexity use cases (like document processing, translation, or sentiment analysis) are perfect for early AI successes. Finally, we’ll discuss the importance of beginning at the department level and making AI a natural part of your design process. By focusing on clear, actionable steps and avoiding unnecessary complexity, you can dip your toes into

Runtime AI brings AI-powered capabilities directly into the execution of a Nintex Workflow or App. Unlike design-time AI, which assists with building workflows, Runtime AI enhances how your live workflows operate by analyzing content, generating summaries, detecting entities, and making light, context-aware decisions as the workflow runs. Runtime AI Actions are lightweight, single-step automations that use large language models (LLMs) such as GPT and services like Azure Document Intelligence to perform specific content generation or analysis tasks. They are easy to configure and fit naturally into workflow execution, allowing you to add intelligence without complexity. All actions are delivered through the Runtime AI Platform Service and are accessible via API for integration across Nintex products. In this release, there are 11 out-of-the-box actions available in Nintex Workflow. Videos