Catching contamination before the crisis.
AquaAccess unifies IoT telemetry, geospatial analytics, institutional datasets, and community reports into a single situational-awareness layer for water systems. Agencies see risk forming — they stop reading about it after the fact.
The problem
Water utilities and regulators sit on rich data — sensor telemetry, lab results, historical flow rates, community complaints — but the data lives in silos that don’t speak to each other. By the time a contamination or infrastructure failure surfaces, the response window is already closing. Executive dashboards, field operations, policy analytics, and sustainability reporting each need different views of the same underlying truth.
Our approach
AquaAccess is a cloud-native environmental-intelligence platform built on three principles:
- Fuse everything, then reason. Sensor telemetry, geospatial layers (GIS/PostGIS), institutional datasets, and community reports flow into one unified model before any analytics runs.
- Detect early, route automatically. Anomaly-detection and risk-scoring models identify contamination events, degradation signals, and supply disruptions — automated incident routing gets them to the right responder within minutes.
- Secure by construction. Enterprise-grade controls, encrypted data interchange, PKI credentialing, and governance aligned to ISO 27001 and NIST AI RMF — not retrofitted later.
System architecture
- Edge. Field sensors communicate via MQTT and CoAP; edge inference handles preliminary anomaly detection before data hits the cloud.
- Ingestion. Azure IoT Hub and AWS IoT Core normalize telemetry; event-driven microservices fan the stream out to analytics, alerting, and storage.
- Intelligence. Transformer-based data-fusion models and risk-scoring produce contamination probabilities and infrastructure-degradation signals.
- Delivery. Executive dashboards for leadership, field-ops views for on-site crews, policy analytics for regulators, and sustainability metrics for ESG/SDG reporting — all from one data model.
- Governance. Secure API gateways, MITRE ATT&CK-aware threat modeling, and audit logs alignable to ISO 27001 and NIST AI RMF.
Tech stack
Why it mattered
Operators stopped switching between four systems to diagnose one event. Regulators got policy-grade analytics from the same source the field team was acting on. And the platform was structured so future data sources — satellite imagery, weather feeds, regional sensor networks — could plug in without re-architecting.