Intercom powers realtime conversations between businesses and their customers at global scale. Those conversations now increasingly include AI, with customers expecting fast, seamless responses that feel as reliable as the rest of the product.
For years, Intercom used an in-house realtime system called Nexus to support experiences like chat updates, presence, and typing indicators. Nexus served the company well for that era of the product. But as Intercom's needs evolved, particularly with the growth of Fin, its AI customer service agent, the team needed a different model for realtime delivery.
Rather than continue investing in infrastructure that wasn't core to Intercom's differentiation, the team chose to partner with Ably. The result was a more dependable foundation for AI-powered conversations, a simpler path for delivering realtime message data, and more engineering focus on the product experiences that matter most to customers.
The challenge: AI changed what Intercom needed from realtime
At Intercom, realtime has always been central to the customer experience. Conversations need to move quickly and feel responsive across devices, regions, and channels.
For a long time, Nexus was a good fit for that job. It was designed for a world where lightweight signaling was enough to keep clients in sync and support the messaging experiences Intercom needed to deliver.
That changed as the product evolved.
Colin Kennedy, Principal Product Engineer at Intercom, saw this shift play out directly. "With AI, interactions are actually in realtime, as opposed to delayed responses from humans. Therefore realtime connections matter even more. A dropped connection can mean that users lose entire AI responses with detailed information. That's unacceptable.”
The rise of AI made realtime delivery more critical. With Fin, Intercom wasn't just updating interfaces or signaling that a conversation had changed. The company was building experiences where users expected answers to arrive fluidly and reliably, with no gaps, stalls, or ambiguity.
That raised the bar for what the underlying infrastructure needed to do. Intercom wanted stronger delivery guarantees, more confidence in how message data reached clients, and a foundation that could support the next generation of AI-driven customer conversations.
Just as importantly, the team recognized that building and maintaining that foundation themselves was no longer the best use of engineering time.
