IntelPol
Smart Policing Software for Crime Prediction and Analysis
- SOLUTION
IntelPol
IntelPol is a AI-powered Crime Prediction and Analysis Software that built for Law Enforcement Agencies (LEAs) to observe crime trends using the existing police database and provide comprehensive and accurate predictions of when & where crimes are most likely to occur next.
Traditional Policing relies on reactive responses to criminal activity, which leads to inefficient resource allocation and missed opportunities for crime prevention.
IntelPol allows police departments to shift from a reactive to a proactive approach of policing by utilizing advanced AI & Geospatial technology for analyzing and predicting crime, thereby assisting the police officers in making informed decisions.
It has been successfully implemented by Dubai Police since 2022, resulting in a 25% reduction in alarming crimes and a 7% decrease in non-alarming crimes in 2023
- CORE FEATURES
How It Works

MAP
Map Crime Resources

ANALYZE
Hotspots Clusters Heatmap

PREDICT
Crime type + Location + time

ACT
Optimized Resource Allocation

MEASURE
Crime Trends Sys Utilization Accuracy
The Solution Requires
Mandatory
Location
Date & Time
Category
For Accurate Predictions
Demography
Criminal Tactics
Weapons Used
The Solution Requires
Mandatory
Location
Date & Time
Category
For Accurate Predictions
Demography
Criminal Tactics
Weapons Used
Key Capabilities
- Identifies Patrol Units’ locations at the time of incident and suggests routes for patrolling units.
- Accurately predicts the crime through automated geospatial analysis using historical crime data
- Identifies crime-prone areas, timeframes, and behavioral patterns
- Generates precise crime predictions with actionable insights, narrowing forecasts to specific 3-hour windows over a 3-day period with exact location details.
- Supports in efficiently planning the routes of patrols to ensure that the resources are used effectively
- Generates statistics and reports based on crime happening in different geographic regions.

