AHA Catch

The Challenge

AHA coordinates the UK's response to the invasive Asian hornet. Their monitoring relied on fragmented spreadsheets with delayed reporting and no centralised field view. Field workers submit data from hedgerows and rural locations on mobile devices with intermittent connectivity. The system needed to serve three distinct user roles — field workers needing fast submission, analysts needing data verification tools, and coordinators needing real-time geographic overviews — in a single application.

Our Approach

• Mobile-first, field-first design with large touch targets, minimal text input, and camera-native image capture for single-handed operation in outdoor conditions.
• GraphQL API layer serving three distinct user roles with different data requirements from a single endpoint — lightweight payloads for field workers, rich filterable datasets for analysts.
• Interactive mapping as a first-class feature with custom marker clustering, real-time data overlays, and geographic filtering built to handle hundreds of concurrent data points.
• Progressive data submission with local queuing and background sync for unreliable field connectivity.
• Role-based access with interface adaptation — one application, one URL, three tailored experiences.

The Outcome

Catch replaced AHA's manual workflow with a unified platform. Field workers submit sightings directly from the field. Analysts verify in real time. Coordinators have a live geographic view of the entire network. The time between sighting and coordinated response has been significantly reduced, and data quality has improved through structured capture and built-in verification.

Key Takeaways

• Device-adjacent interfaces require device-adjacent thinking — designed for the hedgerow, not the office.
• Multi-role applications benefit from GraphQL's query flexibility, adapting data to the consumer.
• Full-service delivery removes the client's technical burden — Pendulum owns the entire lifecycle.