AppsPro is The Market Leader in Predictive Policing
AppsPro has a precise definition of predictive policing. For us and our customers, it is the practice of identifying the times and locations where specific crimes are most likely to occur, then patrolling those areas to prevent those crimes from occurring. Put simply, our mission is to help law enforcement keep communities safer by reducing victimization.
Our day-to-day operations tool identifies where and when crime is most likely to occur, enabling you to effectively allocate your resources and prevent crime.
The data we use for our predictions is very important. We make our predictions based only on victimization information, i.e. crimes that have been reported to police. This information is anonymized; no personally identifiable information is ever collected or used. We believe that protecting the privacy and civil rights of the residents of our communities is as important as protecting them from crime.
The History of AppsPro
AppsPro grew out of a research project between the Los Angeles Police Department and UCLA. The chief at the time, Bill Bratton, wanted to find a way to use COMPSTAT data for more than just historical purposes. The goal was to understand if this data could provide any forward-looking recommendations as to where and when additional crimes could occur. Being able to anticipate these crime locations and times could allow officers to pre-emptively deploy officers and help prevent these crimes.
Working with mathematicians and behavioral scientists from UCLA and Santa Clara University, the team evaluated a wide variety of data types and behavioral and forecasting models.
The models were further refined with crime analysts and officers from LAPD and the Santa Cruz (California) Police Department. They ultimately determined that the three most objective data points collected by police departments provided the most accurate input data for forecasting:
- Crime type
- Crime location
- Crime date and time
The current Appspro platform represents a significant investment of over 70 research-years of PhD-level analysis, modeling and development. It has undergone over a million hours of officer testing in departments of all sizes around the world.