What I joined and what I was asked to build
TSC Labs is a B2B intelligence company serving enterprise teams in government affairs, corporate communications, public affairs, and sustainability. Their existing product had the right data and the right intent, but the product design wasn't keeping pace with what clients needed it to do. The user interface was fragmented, the information architecture made it hard to move between related pieces of intelligence, and the AI layer was bolted on rather than designed as a core part of the experience.
I was brought in as Lead UX/UI Designer to redesign Genie from the ground up. The brief wasn't to improve individual screens — it was to rethink what the product fundamentally was and how it worked. That meant starting with the problem the product was solving, understanding the people who used it, and then designing everything: the information architecture, the interaction model, the design system, and every individual feature area.
8
Major feature areas designed from scratch
1M+
Stakeholders in the platform database
30+
Global markets covered
2 yrs
End-to-end design ownership
Platform Feature Areas
Media & Signal Monitoring
Global media feed, issue tracking, geo heatmap, sentiment analysis
Profiles & Engagement
1M+ stakeholder database, profile management, groups, notes, touchpoints
Dashboards & Insights
Configurable widget dashboards, issues view, geographic intelligence
Ask Genie
AI co-pilot for stakeholder & issue intelligence, briefings, analysis
Engagement Plans
Project-based engagement planning, activity tracking, milestones
Networks
Visual relationship mapping, path discovery, NGO network analysis
Enterprise teams were drowning in information and starving for intelligence
The organisations that use Genie operate in environments where external signals matter enormously. Regulatory decisions, NGO campaigns, media narratives, stakeholder positioning: all of it affects strategy, and the teams responsible for managing it are trying to do so across dozens of markets, in multiple languages, with a stakeholder pool that can run into the thousands.
The tools they were using before weren't built for this. Media monitoring platforms generated enormous volumes of content with no way to separate signal from noise. Stakeholder management happened in spreadsheets, in CRMs designed for sales pipelines, or in consultancy reports that were already outdated by the time they were delivered.
What these teams actually needed wasn't more data. What they needed was a platform that could help them make sense of it — connecting media intelligence to stakeholder profiles, tracking issues over time, and bringing AI-generated analysis into the same workflow.
Before Genie
- Media monitoring tools with high noise, low signal
- Stakeholder records in spreadsheets or sales CRMs
- ESG reports compiled manually twice a year
- NGO network research outsourced to consultants
- No connection between media coverage and stakeholder context
- AI analysis in a separate tool, insights lost between sessions
With Genie
- Continuous issue monitoring filtered for relevance
- Centralised stakeholder profiles with engagement history
- Disclosure-ready reporting from the same daily workflow
- Visual NGO network maps built and maintained in-platform
- Media coverage linked directly to stakeholder profiles
- Ask Genie AI insights saved and traceable on the profile
Who uses Genie — and why designing for all of them required deliberate choices
One of the most important things I did early on was resist the temptation to design for a generic "enterprise user." The people who use Genie have fundamentally different goals and fundamentally different relationships with information, and collapsing them into one persona would have produced a product that served nobody particularly well.
The Signal Analyst
Tracks what's happening and surfaces it for others. Needs to move through high volumes of media coverage quickly, produce briefings that are accurate and timely. The Insights, Issues, and Ask Genie briefing features were designed primarily with this person in mind.
The Engagement Manager
Manages relationships. Preparing for meetings, tracking engagement history, maintaining context on hundreds of stakeholders across multiple markets. For them, the product needs to be a reliable record — somewhere they can store what they know, find it quickly, and share it with colleagues.
The Strategy Lead
Needs to see the landscape, not just individual signals. Asking questions about how issues are evolving, which NGOs are connected to which campaigns, how reputation is tracking across regions. The dashboard layer, network mapping capability, and geographic intelligence view were designed for this way of working.
The platform had to work as a continuous intelligence system, not a series of point-in-time reports. Every design decision was evaluated against that: does this help users build an ongoing picture, or does it produce a snapshot that goes stale?
Start with the information architecture. Everything else follows.
The single most important design decision I made on Genie wasn't about any individual screen. It was the choice to make issues the organising principle of the platform. Not stakeholders. Not media coverage. Issues — the topics, risks, and narratives that a team is tracking — as the thread that connects everything else together.
In the new architecture, issues provide the connective layer. A stakeholder profile shows which issues that person has been commenting on. A media alert is tagged to the issues it relates to. A dashboard widget tracks issue salience over time. Ask Genie can be asked about a specific issue and return analysis drawing on both media coverage and stakeholder profiles simultaneously. This connection is what turned a collection of features into a platform.
How I approached the work
Map information flows first
Spent the first weeks understanding how intelligence actually moved in client organisations — what was the daily workflow of an analyst, what did an engagement manager need before a major meeting. These conversations revealed the gaps and shaped every subsequent design decision.
Design navigation before any feature
Getting the navigation right meant users could find things predictably and move between related areas without losing context. The left nav became a consistent anchor point, with key sections always accessible regardless of which feature area you were in.
Build the design system in parallel, not after
GENIE DS was built alongside feature work rather than as a separate project. Every component designed for a specific feature was abstracted into the system at the same time — so the system reflected real usage patterns rather than theoretical ones.
Design Ask Genie as part of every workflow
Ask Genie is available on the stakeholder profile, accessible from the media feed, embedded in the dashboard, present in the network view. It appears contextually — when there's relevant intelligence to surface, it surfaces it; when there isn't, it stays out of the way.
Eight feature areas — each designed as a coherent system, not a collection of screens
Media & Signal Monitoring
The challenge wasn't building a media feed — it was making one useful for people already overwhelmed by media. I designed the My Feed surface around workspace-scoped content so teams only see coverage relevant to the issues and stakeholders they're tracking. Every article is linked to the issues it relates to rather than existing in isolation. Filters, saved views, and issue-based organisation were designed as first-class features.
Stakeholder Profiles & Engagement
The most-used surface in the platform, and the one with the most design iterations. The core challenge: a stakeholder profile needs to serve two completely different use cases simultaneously. Preparing for a meeting — you need to skim fast. Doing research — you need to go deep. The design separates these two modes visually: key context surfaced at the top, deep-dive content organised below.
Ask Genie — AI Co-pilot
I designed Ask Genie around three principles: it should always cite what it's drawing on, it should be accessible from the context where the question is most likely to arise, and it should produce outputs that can be directly used in downstream workflows — saved to a stakeholder note, shared as a newsletter, or forwarded as a briefing — without additional reformatting.
Contextual Availability
Accessible from the media feed, stakeholder profile, network canvas, and dashboard — not only from a dedicated chat page.
Cited Intelligence
Every AI response shows the sources it drew on. Users can verify claims and trace analysis back to original coverage.
Persistent Outputs
Ask Genie analysis saved directly to a stakeholder profile — creating a longitudinal record of AI-generated intelligence over time.
Brief Generation
Power briefs enable rapid intelligence summaries on emerging issues without requiring a dedicated analyst for each theme.
What Genie looks like when it's working
One of the most instructive examples of the product design getting the right things right was a major natural resources company whose sustainable development team managed ESG intelligence, stakeholder engagement, and disclosure reporting across operations in more than ten countries, in four languages.
Before Genie: twice-yearly manual compilation of engagement reports from regional teams, each using different formats. Board-level ESG reporting assembled from scattered inputs. External consultants engaged periodically to map NGO networks — expensive, slow, and outdated when the reports arrived.
What they built with Genie was a continuous intelligence operation. The disclosure reporting problem dissolved almost entirely. The same daily intelligence workflow the team was already using produced outputs that aligned with their Section 172, CSRD, and GRI reporting requirements. There was no separate reporting process anymore.
Daily
Issue monitoring (was periodic)
Live
NGO mapping (was annual consultancy)
On-demand
Disclosure reporting (was twice-yearly manual)
"What began as a centralised ESG intelligence platform has become the operational backbone for the global sustainable development function."
What I learned building a platform from scratch
The most important thing I learned is that information architecture is product strategy. The decision to make issues the organising principle of Genie wasn't a narrow design decision — it was a product decision that determined what the platform could do and who it could serve. Getting that right required deeply understanding the problem space before touching a design tool, and being willing to spend time on questions that didn't produce any visible output for weeks.
The second thing: a design system built in parallel with feature work is a fundamentally different thing from a design system built after. GENIE DS was grounded in real usage from the start, and the system and features evolved together rather than the system being retrofitted to features that weren't designed with it in mind.
The third — and the one I think about most — is how much the product's value depended on the connections between features rather than the features themselves. Any individual part of Genie is useful. But the reason the product works for enterprise clients at scale is that these things connect. Designing those connections — the information flows between features, not just the features themselves — was the hardest and most important part of the work.