InfoAssist

An enterprise AI knowledge platform for customer support and internal agent workflows.

KEY SUCCESSES

AGENCY
Architech

CLIENT
Rogers

InfoAssist was created in response to a major enterprise transition: following Rogers’ acquisition of Shaw, customer support teams were operating across two active knowledge systems with different structures, duplicated content, and inconsistent search experiences. The opportunity was not just to consolidate platforms, but to create a single AI-grounded knowledge experience that could support agents more effectively in the moment and establish a foundation for future AI-enabled service tools.

30-40%

Reduction in agent search time.

10%+

Decrease in agent handling time

ROLE I PLAYED

  • Product direction

  • Cross-functional alignment

  • Research planning

  • Experience strategy

  • Design direction

  • Component library creation and governance

  • Brand design

  • UI design

The challenge

The product needed to support multiple agent groups, including call centre, technical support, field sales, telesales, and back-office teams, across both west (Shaw) and east (Rogers) operations. Support teams were working across fragmented knowledge ecosystems, one legacy platform was approaching decommissioning, and long search times were increasing handling time and offshore support cost.

The challenge was as much organizational as it was product-based. Migrating two systems required balancing business goals, operational continuity, legacy constraints, and rapidly evolving AI interaction models. The work also needed to establish trust in AI-assisted answers, strengthen the content model behind those answers, and create a path toward a more unified support experience across brands.

What Needed to Happen:

  • Create a unified experience for multiple support channels.

  • Ensure AI answers were traceable to source content.

  • Support migration from both legacy platforms without disrupting live operations.

  • Strengthen the content foundation for reliable AI grounding and long-term governance.

  • Help define a connected identity for the emerging Assisted portfolio of internal AI tools.

The solution

The design strategy focused on a unified experience that could absorb content and workflows from both environments while introducing a more conversational, AI-assisted model for finding answers.

This was not simply an interface redesign. It was a transition strategy that helped Rogers move from fragmented knowledge management toward a more scalable, intelligent support ecosystem. The experience needed to work across multiple agent groups while giving teams a clearer, faster way to find verified answers in the flow of work.

Early testing also showed that interface improvements alone would not produce trustworthy AI outputs. The structure, quality, and hierarchy of the underlying content had a direct impact on answer quality, and weak source content was contributing to poor results and hallucinations. A major part of the work therefore shifted toward strengthening the content foundation through redesigned templates, article models, and content patterns so material from both systems could be restructured and migrated more effectively. This helped create the conditions for more reliable AI performance, centralized governance in Contentful, and a stronger long-term knowledge ecosystem.

Building the brand for an internal AI portfolio

As the platform evolved, it became clear that the experience required more than usability alone. It also needed a distinct identity that would help both users and stakeholders understand it as part of a broader shift in how internal tools were being modernized. Alongside the product work, I helped shape a visual language for the emerging Assisted portfolio so these tools would feel connected, intentional, and future-facing.

Leadership impact

For Rogers, the work helped move the organization toward a more unified operational model for support knowledge, strengthened the systems required to make AI outputs credible, and created a clearer foundation for future internal AI tools. The platform reduced agent search time by 30–40% and contributed to a 10%+ decrease in handling time, while introducing source-traceable AI answers, centralized content governance in Contentful, and migration of knowledge content ahead of platform decommissioning to reduce technical debt and operational risk.

For Architech, the engagement became a showcase for high-maturity UX delivery in complex AI and enterprise transformation work. I scaled the design capability from a single designer to a full design pod—two product designers, two content designers, and one researcher—focused on modernizing content for AI-ready frameworks and guiding authors through updated patterns. This team, which I oversaw, significantly increased the agency’s design-led revenue on the account and raised the overall UX maturity of delivery, positioning Architech as a partner capable of leading large-scale, AI-enabled service transformations.

“Thanks for always having your finger on the pulse”

— Director, AI Self Serve & Agent Tools for Rogers Digital

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