Haliviq
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Department of Water Resources: AI Module for a Field-Officer Mobile App

The Department of Water Resources already relies on a mobile app and wanted AI added to it. That makes this less a new-app project and more a question of connecting a model to live agency data without breaking something people depend on every day. Haliviq built the AI module, extended the existing systems behind the app and integrated the result into the workflow field officers use. We worked from the department's own water resource data and tested on real operating scenarios. Here is what we delivered, how we worked and the technology involved.

Industry

Government & Public Sector

Platform

Mobile App (iOS & Android)

Year

2025

Services

4

Services Provided

Mobile App DevelopmentAI Module DevelopmentWater Resource Data AnalysisLegacy System Extension
Department of Water Resources

Project Objectives

  • Add a specific AI capability to an operational government workflow.
  • Analyse water resource data with the AI module, using live agency data in place of a static dataset.
  • Extend the department's legacy systems instead of replacing them.
  • Keep the system reliable enough for field officers to depend on every day.
  • Design the app screens around how field work is actually done.
  • Make the module extendable and retrainable as requirements change.

What We Delivered

  • An AI module built for a specific analysis or verification task
  • Mobile app integration connecting the AI module to field workflows
  • A water resource data analysis capability within the app
  • Integration with the department's existing and legacy data systems
  • Reliability and accuracy testing against real operational data
  • Field-operations UX design for the screens officers use
  • Documentation and handover for ongoing maintenance by the department

How We Built It

1

Operational and data discovery

We studied the workflow as it exists and the data the AI module needs to read. Understanding what officers do in the field decided where AI could help without getting in the way.

2

AI module development

We built and tuned the model for the specific analysis task required. We kept it scoped to one clear job so its behaviour can be checked and explained.

3

Mobile integration

We integrated the module into the app that field officers already use daily, and connected it to the department's data systems. Officers keep working in the same place.

4

Validation and handover

We tested against real operational scenarios and handed over documentation. The department can maintain, retrain and extend the module afterwards.

Technology & Tools

AI/ML module development, built for one defined analysis taskMobile app integration layer, connecting the module to the officers' appLegacy system and database integration, extending existing systemsCloud infrastructure for model inferenceSecure data-handling architecture for agency dataField-operations UX design

Results

  • The new app adds AI capability to a system field officers use operationally.
  • The AI module works with live agency data rather than being tested in isolation.
  • The workflow is built to be reliable enough for daily field use.
  • Legacy systems are extended in place, not replaced.
  • The module can be retrained or expanded by the department over time.

FAQ

Short answers about this project.

AI-enabled government mobile projects like this typically take two to four months, depending on how complex the integration is.

A purpose-built AI/ML module integrated into a mobile app and connected to the department's existing systems through a secure data-handling architecture.

The department depends on its current systems every day. Extending them keeps what works, avoids a risky switchover and lets the new capability arrive sooner.

We tested the module against real operational scenarios and data, not only sample data. Accuracy and reliability matter because field officers use the results in their work.

Yes. It was built to be extended or retrained as requirements change, and documentation was handed over for the department's own maintenance.

Yes. Adding an AI module on top of an existing system suits agencies that want to modernize in place instead of rebuilding from scratch. The scope depends on each agency's data and workflow.

Read the Full Case Study

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