A Big Data Siren For Law Enforcement Intelligence

Big Data – Law enforcement officers, detectives, private investigators and military intelligence staff have used an increasing amount of technology over the years. Forensic fingerprinting arrived around 100 years ago, the first crime laboratories were established in the 1920s and the introduction of the two-way radio came not long after.

Modern policing technologies include in-car laptop computers, Optical Character Recognition (OCR) systems, drones and a variety of body-mounted equipment such as smartphones, cameras and GPS systems. With many of these technologies built to ruggedized standards, could the next weapon against crime be a softer software-based set of solutions?

Big data for cops

Galway, Ireland and Philadelphia-based company Siren thinks its approach to big data crunching could make a difference. Its technology is aimed at investigative functions within intelligence organizations (cyber threat intelligence, financial crime, law enforcement) and combines advanced link analysis, Business Intelligence (BI), big data monitoring, operational intelligence monitoring, data discovery and search.

As well as law enforcement, Siren also targets the financial services, life sciences and telco markets — so what has been the problem to date and how does this company claim to be able to offer a new approach?

“In law enforcement today, there are many fragmented technology tools — and this is a problem. Investigators use record management systems but often use separate graphical tools to draw connections as part of the ‘link analysis’ phase [when trying to pin down suspects]. The prevalence of disjointed software in many departments does not positively enhance the investigative process. Rather than act as an informative discovery process, no new information comes to the surface that investigators didn’t know already. Investigative Intelligence, via Siren, is the ability to fuse previously disconnected analytics capabilities so that the investigator can freely ask questions – maximizing each individual technique,” said Giovanni Tummarello, chief product officer at Siren.

Siren explains that it approaches these issues by using automatic relationship detection, entity resolution and Natural Language Processing (NLP). The company offers AI-driven associative features and unstructured data handling to try and bring together results.

This article originally appeared on forbes.com To read the full article, click here.

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