01 · Detect & monitor
What now
A live replica of the river and the city — stage, flow, quality, rainfall, and infrastructure — updated as satellite, weather, and in-situ streams arrive.
National Champion · Jal Shakti Hackathon 2025
A living digital twin for rivers and cities
See the system as it is. Forecast what comes next. Test a decision before you make it.
Aurixys fuses satellite imagery, terrain, weather, and in-river measurements — including ADCP current profiles from autonomous vessels — into one hydro-ontology. That model is the operating surface for flood forecasting, river management, and urban water planning.
Recognition and collaborations
What we have achieved
National Champion
Jal Shakti Hackathon 2025
Collaborating with
Ministry of Jal Shakti
Scientific collaboration
NIH Roorkee
Collaborating with
Ministry of Earth Sciences
Platform
One twin. Three questions.
GIS shows a map. A digital twin is a living model: it watches the present, projects the near future, and lets you rehearse a response — on the same semantic fabric.
02 · Forecast
What next
Hydrology and hydraulics, constrained by physics and corrected by ADCP and gauge observations, so operators can see inundation timing and extent before they happen.
03 · Scenario analysis
What if
Test a gate, a pumping plan, or an extreme monsoon against the same twin. Decisions are scored against a model that already knows the system.
Geospatial intelligence core
Hydro-ontology
The hydro-ontology is the semantic framework inside Aurixys Twin. It standardises rivers, terrain cells, vessels, sensors, storms, and city assets — and the relationships between them — so satellite passes, ADCP profiles, gauges, and models can reason over one world. That is what makes integration, scientific forecast, and basin-to-city analytics possible at operational scale.
Data lands continuously. Models stay coupled to physics. Operators receive analytics, scenario runs, and alerts — not a folder of disconnected layers. How the ontology is structured →
Offerings
Built for water, from basin to street.
The same twin, resolved to the decision in front of you — a monsoon forecast on a river, an inundation map on a city, or a current profile taken from the water itself.
From field to forecast
A continuous, multi-source compute problem.
Every basin cell, every urban catchment, every satellite pass and ADCP ping is aligned, stored, and reasoned over as a living graph — then simulated forward under physics-informed models. The twin is not a dashboard on top of files. It is an always-on pipeline that scales with the water system it represents.
01
Capture
Ingest every stream the basin actually produces — continuously, not as a one-off GIS project.
- Optical and radar satellite passes across whole catchments
- Weather nowcasts, rainfall radar, and climate ensembles
- ASV water-quality time series and ADCP velocity profiles
- Gauges, SCADA, GIS layers, and city drain networks
02
Fuse
Align projection, time, and identity so a river reach, a drain, and a sensor refer to the same world.
- Automated georegistration and temporal alignment
- Terrain, hydrology, and built-environment layers in one frame
- Entity resolution from basin scale down to a single asset
03
Understand
The hydro-ontology is the semantic graph of the twin — rivers, cells, vessels, storms, and cities as typed relationships, not disconnected files.
- Shared vocabulary for operators, models, and data pipelines
- Explainable links: what feeds, monitors, and sits on what
- Graph-scale reasoning over years of multi-source observations
04
Forecast
Physics-informed models run forward on the fused state — rainfall to runoff to inundation — and stay honest against live measurements.
- Riverine and urban flood simulation
- Discharge, velocity, and water-quality trajectories
- Confidence bounds, not a single unverified line
05
Act
The twin is an operations surface: dashboards, scenario runs, and alerts that fire when thresholds or forecasts demand a response.
- Analytics for basin and city operators
- Scenario workspaces for planning and drills
- Workflow alerts into existing command systems
Field sensing
The river, measured as it flows.
Satellites see the surface. Models guess the column. Jal Prahari closes that gap: a solar-hybrid autonomous surface vessel that dips a water-quality cage below the film and profiles current with ADCP — acoustic beams that read velocity through the depth of the channel.
Those observations bind to ontology entities in the twin. Discharge, flood routing, and water-quality forecast stay honest because they are corrected by the river itself. Field-run on the Godavari and the Ganga.
Jal Prahari field systemsContact
Request a briefing.
For basin operators, city agencies, and partners who need a living model of water — not another static map.
- Vishal@aurixys.com
- +91 70384 86909
- LinkedIn — Vishal Patil
- Nashik, Maharashtra, India