Turning Urban Data Into Intelligent Action

Ingest, model, and optimize. We provide mission-critical infrastructure data and AI-driven congestion management for smart cities, DOTs, and enterprise logistics.

Live Network Congestion Index
7.6B+
Telemetry Points Daily
6%
Avg. Congestion Reduction
45+
Municipal Partners

Core Capabilities

An end-to-end intelligence suite for urban infrastructure.

Big Data Analytics

Ingestion, processing, and analysis of massive, real-time datasets including sensor feeds, IoT arrays, and GPS telemetry at true enterprise scale.

Traffic Modeling

High-fidelity simulation and predictive modeling of vehicle and pedestrian flow under complex conditions, weather events, and structural changes.

Congestion Management

Real-time bottleneck detection, adaptive signal control overrides, and automated incident response tools designed to slash travel times and emissions.

Advanced AI Analytics

Deep learning computer vision for vehicle detection, anomaly tracking, and LLM-powered natural language reporting overlays for operational commands.

Platform Deep Dive

Traffic Modeling & Simulation

Move beyond static origin-destination matrices. DataNomic Labs utilizes continuous macroscopic traffic flow models based on the kinematic wave theory, incorporating conservation equations such as $ \frac{\partial \rho}{\partial t} + \frac{\partial (\rho u)}{\partial x} = 0 $ to calculate density ($\rho$) and flow velocity ($u$) across vast municipal grids in real time.

  • Synthetic Data Generation: Stress-test urban grids using agent-based modeling before laying a single brick.
  • Event Forecasting: Predictive flow adjustment for concerts, sporting events, or severe weather conditions.
  • Emission Modeling: Map speed and stop-and-go patterns directly to localized CO2 output models.
Traffic Modeling Node Diagram
Node Active
Simulating 45,000 entities

Platform Architecture

A robust, scalable pipeline moving from raw endpoints to actionable operational intelligence.

1. Ingestion

IoT Sensors, CCTV, GPS, 3rd-Party APIs

2. Processing Cloud

Kafka Streaming, Data Normalization

3. AI / ML Engine

Computer Vision, Predictive Analytics

4. Outcome API

Dashboards, Signal Overrides, Policy

Proof of Impact

Real-world deployments. Measurable results.

City traffic
Midwestern Metro Authority

Adaptive Corridor Synchronization

The Problem

A major 12-mile arterial corridor was experiencing severe gridlock during rush hour, compounded by unpredictable freight rail crossings.

Our Approach

Deployed DataNomic's ML-driven signal override system, integrating real-time API feeds from rail operators with existing municipal loop detectors.

-22%
Commute Time
-14%
Idling Emissions
Logistics map
Tier 1 Logistics Enterprise

Last-Mile Routing Optimization

The Problem

Static routing software could not account for micro-weather events or spontaneous urban bottlenecks, leading to missed delivery SLAs.

Our Approach

Integrated our continuous anomaly tracking API directly into the client's fleet management software for dynamic rerouting.

99.8%
SLA Compliance
+$4.2M
Operational Savings