Agent Assist
Enhancing customer support agents day-to-day with modern agentic workflows
Agency
Architech
Role
Design Lead
Client
ROGERS
Year
2025 - 2026
Agent Assist is an internal Rogers product designed to lower Agent Handling Time (AHT) by giving customer support agents proactive, timely context as a call begins and continues. It brings together information from multiple sources, including account details, prior interactions, transfer context, network health, order activity, and other signals, so agents can respond faster without switching across systems. For customers, that means less repetition and a smoother handoff experience; for the business, it means a more efficient support operation with clear cost implications tied to AHT.
As Design Lead, the role extended beyond interface design into product direction, stakeholder alignment, and workflow strategy. Working closely with Product Managers and Product Owners, the work helped shape requirements and roadmap direction, while aligning design decisions across customer support, operations, engineering, content, design systems, the virtual assistant team, the main customer support tool, and the knowledge platform team. The project also sat inside a broader internal Rogers ecosystem, where consistency across agent tools, trust in AI-assisted recommendations, and long-term workflow evolution were important secondary goals.
Reframing the product around real agent behaviour
One of the most important insights came from observing how agents actually worked. The original version of Agent Assist lived inside Genesys, the call-handling platform, but analytics showed low usage and call-listening sessions revealed why: once a call connected, agents often left Genesys and worked elsewhere until the call ended. That meant they were missing the very insights Agent Assist was designed to provide, weakening both adoption and operational efficiency.
To address that gap, several directions were explored, including a standalone floating application that could remain visible across the desktop. That concept was selected and developed into a new shell for the same underlying product, allowing agents to stay in their natural workflow while still receiving proactive support. The standalone direction strategically did more than improve visibility, it helped move Agent Assist toward a more flexible platform for future integrations.
The standalone product had to remain useful without becoming disruptive. Screen real estate was limited, the window had to coexist with other critical tools, and proactive notifications needed to be noticeable without overwhelming agents during live calls. This led to the design of several new interaction patterns, including draggable window behaviour, a minimized “listening mode,” subtle motion to reassure agents the tool was still active, and silent triggered notifications that could surface new insights without relying on audio. Figma Make was used to concept these interactions to life, which helped communicate functionality to engineering, get stakeholder approval, and reduce adoption risk by testing a major workflow change before build.
Enhancing the agent workflow even more.
The standalone move also created a stronger foundation for expanding the product. Interaction Wrap-ups, previously a separate module, were incorporated into the standalone environment to give agents quick access to summaries of recent calls and notes that could inform the current interaction. This reduced reliance on Genesys and helped normalize the standalone tool as a central part of the workflow.
Extending the platform through modular features
Residential Diagnostics built on an existing wireless diagnostic model but had to accommodate different realities, including known outages, nearby outage reports, in-home modem and extender signal strength, and more complex residential product sets such as modems, IoT devices, and cameras.
Order Status was designed to surface active orders immediately when relevant, giving agents a probabilistic signal for why the customer might be calling. That work also required cross-team alignment on status language and colour usage so agents would see the same story across tools, and the shared taxonomy created here was later adopted more broadly.
Leadership impact
The contribution was not only in designing features, but in helping define how an AI-assisted support product should fit into the realities of live agent workflow. The result was an experience with strong executive support, a clearer path for future modules, and a more strategic foundation for how proactive assistance can be delivered inside Rogers’ support ecosystem.
“Agent Assist is world class”
— SVP Digital at Rogers Digital