The Agentic Reasoning Cycle
Watch the Agents Reason in Real-Time
Select a scenario and step through the agentic reasoning cycle — Sense → Understand → Decide → Act. See how the same four-agent architecture handles floods, dam failures, and traffic gridlock with different physics data.
Interactive Simulator
The agentic cycle in action
Three pre-built scenarios using domain-realistic data. Click Play to auto-advance, or Step through manually. Inspect each stage to see agent reasoning.
01 — Sense / Data Ingestion
Ingesting real-time environmental feeds
Rainfall (6hr)
78 mm
Soil Saturation
0.98 / 1.0
River Level
7.4 m
Forecast Horizon
48 hr
After Act, the cycle loops back to Sense — continuously
The Cycle
Four stages. One loop. Continuous operation.
Sense
Real-time ingestion from satellite, IoT sensors, weather feeds, SCADA systems, and operational data. Agents receive a continuous stream of physical-world state.
Understand
Monitoring and Prediction agents apply domain physics models — hydrology for floods, structural FEM for infrastructure, traffic flow for mobility — grounding reasoning in physics.
Decide
Reasoning and Decision agents synthesize physical understanding into risk assessments. Anomalies are prioritized. Recommendations generated with confidence intervals.
Act
Automated alerts dispatched, dashboards updated, response workflows triggered. Agents loop back to Sense immediately — no manual restart required.
Why Autonomous Matters
Speed, explainability, and continuous operation
Speed
Minutes, not hours
Agents operate continuously. Anomaly detection happens in the current cycle, not the next shift.
Explainability
Physics grounds every decision
Agents don't hallucinate. Every recommendation traces back to a physical model and a measurable input.
Reliability
No manual restart required
The cycle loops automatically. After Act, agents return to Sense without human intervention.
Ready to explore the platform architecture?
See how the four layers — ingestion, physics, agents, application — fit together