Teams | Collaboration | Customer Service | Project Management

Trafikverket, the Swedish Transport Administration went live with federation on Rocket.Chat, chatting directly with Försäkringskassan, the Swedish Social Insurance Agency, which runs another Matrix-based platform. Neither agency moved to a shared platform or routed messages through a third-party bridge. Each kept its own deployment, its own admin console, and its own security posture, and users on either side can now open a conversation with the other agency as if they were on the same system.

There are three different things people mean by “Zendesk MCP”. Before comparing the options, it’s worth separating out these different use cases.

InvGate AI Hub consists of a series of features that enable artificial intelligence for IT teams. From resolving employee requests before they become tickets to monitoring the service environment continuously, acting on every moment of the ticket lifecycle, and assisting agents as they work, it is built to empower support teams and augment their capabilities. The AI Hub is available in all InvGate Service Management and InvGate Asset Management plans, for both cloud and on-premise customers.

AI has delivered a step change in individual productivity across engineering, product, and design. The defining opportunity now is organizational: turning that individual speed into impact a whole team can feel. For most of software’s history, building was the most expensive step, so teams organized themselves around it. AI has turned that on its head.

Every employee opens the same intranet homepage. It doesn't matter what team they're on, what they do, or what they need. The same banners, links, and announcements greet everyone. In trying to be everything for everyone, the intranet homepage ends up feeling relevant to no one.

Without the right context, every day is day one for a coding agent. Agents may have the intelligence needed to write, refactor, and review code, but they still face the same challenge developers do: understanding how complex systems actually work. They need the right context to navigate cross-team dependencies, ownership boundaries, and downstream impacts that are hard to understand from any single workspace. Code only tells part of that story.

A conversational AI Chatbot is an intelligent computer program that mimics real-life human interactions. This is made feasible by the solid basis of machine learning (ML) and natural language processing (NLP). Siri, Alexa, and Google Assistant exemplify the concept of conversational AI. Unlike traditional first-generation bots that deliver canned answers to a set of questions, conversational AI bots are more complex and intelligent.

Understanding the New Normal: Distributed and Remote Workforces With more organizations embracing distributed and remote work models, IT support has become a critical pillar for operational success. The shift to remote work, accelerated by recent global events, has transformed how teams communicate, collaborate, and access company resources. According to a Gartner survey, 47% of companies plan to allow employees to work remotely full-time post-pandemic, highlighting the permanence of this trend.

Historically, sales and customer support have traditionally operated in silos. Teams prioritized acquisition and revenue, while support focused on retention and customer satisfaction, often relying on separate systems with limited communication. The result was a fragmented customer journey and inconsistent experiences. Today, customer experience is a defining competitive advantage. Customers expect seamless interactions, regardless of department, making disconnected workflows increasingly unsustainable.

The past couple of years have changed how my team operates. We’ve experimented, adjusted quickly, and seen meaningful early results. That momentum got me excited about where marketing is headed in the age of AI, even as we continue learning along the way. Since then, we’ve witnessed what holds companies back from succeeding with AI.