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J. Marinho

Case study

Olombongo

Liquidity Radar — collaborative ATM cash map

A collaborative, real-time platform where people report ATMs with cash—helping others skip the city-wide hunt that today happens in WhatsApp groups.

Problem

In Angola, finding an ATM that actually has cash can send anyone into “search mode.” Many people rely on WhatsApp groups to learn where machines still have money—fragmented, noisy, and easy to miss.

Context

Cash availability changes by the hour and by neighborhood. Trust comes from recent, local signal—not from a static bank list. The product needs to feel fast on mobile and honest about what is unverified crowd data.

Solution

Olombongo Liquidity Radar lets users report ATMs with cash in real time and discover what others have shared nearby. The experience centers on a live map, a heatmap of where people search most, report history tied to phone identity, contributor rankings, and collaborative updates as the community feeds the radar.

Architecture

  • Map-first UI with nearby ATMs surfaced from live community reports
  • Heatmap layer highlighting zones where cash searches cluster
  • Report ingestion with phone-based history and contributor reputation
  • Leaderboard and ranking for top reporters to reinforce participation
  • Real-time sync so new reports appear without manual refresh

Technical challenges

  • Presenting crowd-sourced liquidity data clearly without overstating accuracy
  • Keeping map, heatmap, and list views in sync under frequent real-time updates
  • Designing lightweight mobile flows for reporting while moving through the city
  • Balancing validation-phase UX with room to iterate from user feedback

Results

  • A testable product live for idea validation and structured feedback
  • Shift from scattered WhatsApp tips to a single map-based liquidity radar
  • Foundation for collaborative, real-time cash discovery at city scale

Lessons learned

  • The best local products start from a behavior people already have—then remove friction
  • Community data needs transparent UX so trust scales with participation