Case study · Water Resources
Thirty minutes of SQL,asked in a sentence.
The IT subsidiary of the national commission responsible for the country’s longest river system, a basin that supports hundreds of millions of people. The commission oversees water conservancy data, flood management, ecological protection and infrastructure monitoring across the whole basin, and the IT firm runs its data management and work order operations. Traditional workflows created bottlenecks at every point: queries needed professional query languages most staff could not use, so everything went through analysts at over 30 minutes per query.
Constraints and answers
A flood does not wait for an analyst to be free.
One question, and the work order it sets off
Work orders entered by hand without verification
Work orders were entered by hand with no verification standard and no automatic scheduling for emergency response.
Answer
Intelligent data query agent
Everyday questions asked in natural language, answered with generated charts, replacing professional query tools and analyst-led work.
Every question needed an analyst
The tools had too high a threshold: staff could not write query languages, so every question needed an analyst and over 30 minutes.
Answer
Auto-generated work order system
Built-in verification rules classify and schedule emergencies automatically, flood rescue included, cutting entry errors and response time.
No cover outside working hours
Staff numbers were limited and there was no round-the-clock cover, so anything arising outside working hours waited.
Answer
Round-the-clock AI service layer
Support for more than 300 personnel at any hour, covering routine daily operations and emergencies without staffing constraints.
Data and work order systems siloed
Data and work order systems were siloed with no integration, so no process could run automatically between them.
Answer
Integrated data and work order platform
The siloed systems joined into one automated process, so a query can run through to work order execution.
Anyone can ask now, and the agent puts the question to the platform without a query language in between.
The results
Thirty minutes to seconds, at 95% query accuracy.
- 30 min to sec
- DATA QUERY TIME
- Natural language AI agent.
- 95%
- QUERY ACCURACY
- Reliable retrieval for decisions.
- 2%
- WORK ORDER ERROR RATE
- Automated verification and classification.
- 200%
- BETTER SERVICE COVERAGE
- Round-the-clock for 300+ personnel.
- 95%
- FASTER PROCESS EFFICIENCY
- End to end on the integrated platform.
On-premise is not a preference for a river commission. It is the condition of the work.
The stack
What was deployed
Structured storage of water conservancy data, query patterns and work order histories, which is what the agent keeps learning from.
Data management systems, work order platforms and operational tools connected into unified workflows.
Enterprise-grade controls and government compliance protecting sensitive water conservancy and infrastructure data.
Sovereign on-premise infrastructure, keeping full data control and meeting government security requirements.
Примечание о возможностях
Возможности, компетенции и примеры внедрений, представленные на этом сайте, отражают совместную работу ключевой инженерной команды Amanah. Некоторые проекты были реализованы через предыдущие или аффилированные организации. Суверенные внедрения конфиденциальны по мандату, поэтому отдельные клиенты не называются. Соответствующие референсы подлежат проверке в рамках NDA.
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