Introducing Iris Your Automated Dashboard Insights Agent
🟢 LEVEL: INTERMEDIATE TO ADVANCED
From Hackathon to Reality: Meet Iris 👁️
During our Leadership Retreat AI Hackathon in Kenya (November 2025), a cross-functional team set out to solve a universal pain point: "Dashboard Fatigue." We’ve all been in those meetings - the ones that turn into 45-minute screen-sharing marathons where we scroll through charts, leaving only 5 minutes for actual decision-making.
Iris was born to change that. Developed through a brilliant stretch of cross-departmental collaboration, Iris is an AI Agent designed to ensure we never walk into a data meeting "cold" again.
The Team Behind the Tech
Iris is the result of a "sprint" effort by Charity Mbabazi (Head of Tech Product) alongside Emmanuel Kalyebi, Sanogo Aissetou, and Tobias Mulupi. It is a powerful example of what happens when we collaborate across teams to automate the "busy work." Since this started as a hackathon prototype, the team is looking to iterate and expand its capabilities.
What Iris Does:
Auto-Reads Reports: Iris scans Looker Studio dashboards (via email) so you don't have to manually hunt for updates.
Identifies Trends: It compares metrics over time to see where we are growing or stalling.
Flags Anomalies: It highlights what’s "weird" or unexpected in the data before the meeting starts.
Pre-Meeting Briefs: It sends stakeholders a quick summary so everyone arrives with the same context.
The Impact:
✨ Shorter Meetings: Less time "explaining the graph," more time discussing strategy.
📊 Synchronized Context: No more reacting to data in real-time; the analysis is done upfront.
🎯 Consistent Quality: Eliminates "data interpretation roulette" by providing a steady baseline of insights.
📘 Watch the Walkthrough: "Introducing Iris"
We want your input:
How could a tool like Iris change the way your department handles weekly, monthly or quarterly reviews?
Do you have a specific dashboard that is "crying out" for an Iris summary?
Reach out to Charity (charity.mbabazi@experienceeducate.org) and the project team to share your thoughts, suggest a use case, or find out how you can apply similar AI logic to your team’s workflows!