Crisis management
Question
Where will the flood be in 72 hours?
Deceris
Decision → Evacuation recommendation with priorities and sequencing
47 buildings at risk3 bridges to close2 critical infrastructure components
Every operational decision
has consequences.
We show their impact before they become reality. Decision OS for the Physical World
“Where will the flood be in 72 hours?”
Deceris combines environmental data into a single model of reality - predicts events, simulates outcomes, and recommends concrete operational action in advance.
You ask a question. The system gives an answer.
Specific questions. Specific numbers. Actionable recommendations - drawn from a single model of the physical world.
Critical infrastructure
Question
What happens if the levee breaks at km 12.3?
Deceris
Decision → Recommendation: reinforce section 11.8–12.7 km
2.3 km² flood zone890 buildings in range120M PLN estimated losses
Energy
Question
What is the risk profile of our assets for the next 10 years?
Deceris
Decision → Data ready for CSRD report with action priorities
3 locations in high-risk zone+40% probability increase by 203545M PLN/yr estimated losses
Defence
Question
Which routes are available for a heavy convoy?
Deceris
Decision → Route recommendation by operational priority
3 routes with trafficability parameters1 bridge with 20 t load limit+45 min shortest safe alternative
Numbers are illustrative - they show the system’s answer range, not a field deployment.
The physical world is no longer predictable.
Historical data is no longer enough. Manual decisions cost more than ever.
+40%
Extreme weather events
Increase in extreme event frequency over the last decade. Historical models are failing.
60%
Aging infrastructure
Critical infrastructure in Europe is over 40 years old. Degradation outpaces repairs.
2026
Regulatory pressure
CSRD, ESG, flood directive - climate risk reporting obligations grow every year.
89%
Manual decision-making
Organizations managing critical infrastructure still rely on spreadsheets and phone calls.
The cost of one wrong decision is measured in millions.
This is not a concept. It’s a conclusion drawn from real work.
POC with IMGW-PIB
As part of our collaboration with the Institute of Meteorology and Water Management, we worked on predictive models for ungauged catchments - one of the most challenging problems in hydrology.
This experience made one thing clear: turning data into operational decisions is a challenge - not just in hydrology.
- Working with real-world data spanning multiple decades
- Modeling in catchments without monitoring stations
- Integrating environmental data from multiple sources
- Running scenario simulations based on operational data
72 h Forecast horizon
25+ Integrated data sources
Real-time Operational simulations
Deceris in Action.
See how the threat monitoring modules, AI analyst, and vast data catalog execute tasks using a real-world example: Flood Analysis.
Monitor: every threat has a face
Active threats left, stations with alarm level and detection time right. The map follows rivers - Nysa Kłodzka, Ścinawka, Biała Lądecka.
- 8 stations in Alarm, detected 15 Sep 2026, 13:16 UTC
- WILKANÓW, BYSTRZYCA KŁODZKA, GORZUCHÓW and more - with time and severity
- L3 · Active - priority and status at a glance
AEYE · Analyst Assistant
AEYE asks about data, answers with decisions
Built-in analyst in chat. It uses tools that create and modify compute pipelines (Prefect) - the core of the Deceris engine.
- Datasets what is registered and what it contains
- Threats what is monitored and what events were detected
- Analyses & Scenarios impact assessments and what-if variants
- Pipelines & Wizard what computations run and how they are wired
- KPIs scenario vs baseline metrics
Can you list active threats?
One active threat: Flood Warning – IMGW Stations. 8 events, Alarm, 15 Sep 2026.
Which pipeline drives this threat?
Flood Warning pipeline + Inundation Simulation. I can open the wiring or check datasets.
AEYE Assistant goes beyond just reading - it is capable of creating pipelines, connecting datasets, and displaying the computational architecture.
Data: 70 datasets in one catalog
Topographic Objects Database as an organization source. Filters: access, type, state.
The City as a Decision Layer
One model, two scenarios: from routine everyday monitoring to advanced crisis management and evacuation.
Three steps from data to decisions.
From raw environmental data streams to a ready operational recommendation.
01
Data integration
The system automatically combines satellite, hydrological, terrain, and infrastructure data into a single digital model of reality.
02
Physical world model
Based on connected data, the system builds an operational model of the physical world - with history, current state, and change forecasts.
03
Decisions
You ask a question - the system responds with a concrete decision. Based on simulations, scenarios, and recommendations, it tells you what to do, when, and in what order.
The user doesn’t work with data - they work with decisions.
The physical world doesn’t have an operating system. Until now.
A model, not a dashboard
We don’t visualize data. We build a digital model of the physical world where you can simulate scenarios.
Decisions, not analysis
The system gives an answer: what will happen, when, and what to do. It doesn’t leave the user with raw data.
Prediction, not reaction
72 hours of lead time is the difference between controlled evacuation and chaos. Between repair and disaster.
Test before you decide
You can test every decision in a simulation - see the consequences before they become reality.
A decision layer for organizations that operate in the physical world.
Crisis management
Crisis management centers, emergency services, civil protection
Infrastructure
Road, bridge, levee, and energy network operators
Energy & utilities
Network operators, energy companies, natural resource managers
Defence
Terrain analysis, geospatial intelligence, operational planning
Local government
Cities, municipalities, spatial planning offices, climate units
ESG & compliance
CSRD-reporting companies, insurers, funds assessing climate risk
How implementation works
We can start with one region or one use case.
1
Data integration
We connect data sources - satellite, hydrological, infrastructure. Automatically, without manual collection.
2
Region model
We build a digital model of your operational area - with history, current state, and forecasts.
3
First scenarios
We run simulations on your data. You ask questions, the system gives answers.
4
Operational use
The system goes operational - continuous monitoring, forecasts, real-time recommendations.
Contact
See how Deceris works in your area.
We can start with one region or one use case.
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