As law enforcement organizations benefit from readily available online information and databases, they also face the challenge of combing through vast amounts of information, often housed in siloed systems and databases. Across the US, law enforcement teams in state and local government are turning to solutions such as Elastic to save time and improve accuracy as they use data for investigations.

Harris County, Texas, is one such government seeing success with accelerated, consolidated investigative search. Harris County is the third-largest county in the US by population, and it includes most of Houston. With over 70 law enforcement agencies and over 50 fire agencies, the county conducts a large number of investigations, where time is of the essence.

Shing H. Lin, CTO Harris County’s Central Technology Services, developed the Law Enforcement Network Search (LENS) tool, built on Elastic, to help law enforcement agencies in the county quickly find the time-sensitive data they need.

The challenge:

How do we correlate data so law enforcement can find it quickly and easily?

When conducting investigations, law enforcement agencies had to sift through siloed technology and systems, including court data, records management systems (RMS), citations, computer aided dispatch (CAD), license plates, and more.

Typically, teams would perform searches in each database separately, then manually link the data from the different searches together. This process was time-consuming, prone to error, and slowed down critical investigations.

The solution:

Law Enforcement Network Search (LENS) built on Elastic

Initially, when Lin and his team experimented with technology to solve their problem, they found that other products’ licensing limited the number of data sets they could use. They instead turned to Elastic, which was able to pull data from all the sources they needed.

The team built an application that layers on top of Elastic core capabilities, providing an easy way for law enforcement to search across multiple data sources and correlate related information. A single search for a person (such as “suspect male teardrop tattoo”) can pull up 911 call transcripts, an arrest record, associated incidents, and all locations and people linked to the suspect — all in a single view. Within an incident record, users can drill down into 911 call notes, an entire narrative report and supplements, and CAD call details.

Using machine learning (ML) capabilities, the tool is even able to provide recommendations of similar cases, helping agents decrease investigation time by focusing on only the most relevant information.

Users can also conduct a map-based search, which localizes information to a specific precinct or area, again reducing time needed to sift through data.

Learn more

See Lin in action talk about the solution, or to learn more about how search can help your organization, read the public sector white paper Implementing Search for Your Knowledge Base.

Elasticsearch Platform

ELK Stack

Elastic Cloud

Observability

Security

Search

By industry

By solution

Customer spotlight

Developers

Connect

Learn

Help

See what's happening at Elastic

On-demand webinar

What’s Cooking in Kibana? (2016)

Hosted by

Chris Cowan

Rashid Khan

Overview

Register for more webinars

Upcoming webinar

Semantic search excellence: Advanced concepts with AI

Upcoming webinar

Semantic search excellence: Getting started with AI

Upcoming webinar

Fight smarter: Accelerate your SOC with AI

Upcoming webinar

Vulnerability Management and Posture Management

Upcoming webinar

Elasticsearch AI Workshop with Microsoft: Craft Generative AI Applications

Follow us

About us

Join us

Press

Partners

Trust & Security

Investor relations

EXCELLENCE AWARDS