Police Technology Forum 2024

  • March 7th
    • Conference
    • Canberra, Australia

We are excited to be part of the 11th Annual Police Technology Forum 2024 – Australia’s premier law enforcement technology and networking event, held in Canberra on March 7-8, 2024. This conference will highlight the latest capabilities shaping law enforcement in Australia, and globally.

What to expect?

The forum’s focus on data analytics & artificial intelligence presents a unique opportunity for GraphAware to showcase how our solution GraphAware Hume can address the pressing challenges faced by law enforcement and intelligence agencies: the mountains of valuable data in disconnected, siloed systems. We look forward to discussing the latest advancements in graph analytics technology, including the use of Large Language Models and AI for unstructured data analysis, to enhance intelligence capability and bolster national security and resilience.

We are delighted to meet you and discuss the latest advancements in graph analytics technology, such as the use of Large Language Models and AI for unstructured data analysis, to enhance intelligence capability and bolster national security and resilience.

We look forward to seeing you!

Presentation

  • 7th March 2024, 12:00 PM

Graph Databases in Policing: Powerful Link Analysis for Safer Communities

In this session, Dan Newland, our General Manager for APAC region, will present the value that graph database technologies are delivering for law enforcement agencies both in Australia and across the globe. Using real examples from Australian law enforcement implementations, Dan will show the power and efficiency gains that connected data can deliver for law enforcement.

Exhibition

  • Demo

Graph Powered Police Investigation

Stop by our booth to witness how Hume, powered by a graph database, revolutionises police investigations.

Our engineers will demonstrate how Hume seamlessly integrates disparate data sources, employs advanced analytics like temporal and geospatial analysis, and empowers investigators with intuitive visualisations. From identifying prime suspects to monitoring offenders and identifying threats, Hume streamlines the entire investigative process.

Analysts visiting our booth will experience the power of data linkage and complex querying firsthand, discovering how Hume, with its graph database backbone, can enhance their investigative efficiency.

Knowledge graph schema for criminal investigation
  • Demo

Knowledge Graph Extraction from Unstructured Data Using GPT

At our booth, we will also showcase a groundbreaking paradigm shift with Large Language Models (LLMs) utilised for extracting knowledge graphs from diverse unstructured data sources such as documents, judicial reports, investigator reports, and social media posts.

Seamlessly integrated within the Hume data orchestration tool, LLMs empower data engineers to effortlessly integrate them into workflows, significantly reducing the time to acquire knowledge from months to mere minutes. Hume Orchestra harnesses the power of LLMs for entity extraction and relationship identification from text, sculpting a structured graph/network within a production system.

  • Demo

Creating Knowledge Graph from Phone Forensics

We will demonstrate the ingestion of forensic phone extractions and their transformation into a knowledge graph.

Based on information content and graph connectivity, we will select the most relevant target entities. Then, we will extract key information from these target phones using cutting-edge AI, including LLMs. Finally, we will enrich the data using OSINT, providing unique context on the target entities.
Seamlessly integrated within the Hume data orchestration tool, LLMs empower data engineers to effortlessly integrate them into workflows, significantly reducing the time to acquire knowledge from months to mere minutes. Hume Orchestra harnesses the power of LLMs for entity extraction and relationship identification from text, sculpting a structured graph/network within a production system.

Let's Meet