(Winnipeg, MB) IMT is excited to announce a major new release of Intel:ID, completely reimagined to bring compelling investigative analytics and insights to justice, law enforcement, and intelligence agencies of all sizes.
Studies have shown that investigators and analysts can spend up to 80% of their time on collecting and curating data. With IMT Intel:ID entity extraction and advanced entity resolution, analysts can now collaborate and focus on analysis rather than data gathering to improve investigative outcomes.
IMTs next generation Intel:ID solution now includes Senzing Entity Resolution, rich integration to IBM i2 Analyst Notebook and natural language processing for entity extraction from unstructured text.
Mark Holmes, VP of Client Solution Engineering at IMT commented, “Until now, real-time entity resolution and relationship discovery software was complex and expensive keeping it out of reach of smaller and mid-sized agencies. We applied our 20+ years as Identity Solutions Experts to deliver a sophisticated investigative analytics solution to agencies of all sizes. That is a gamechanger.”
IMT becomes a Senzing Partner to bring real-time AI for Entity Resolution
IMT has signed a partnership agreement with Senzing incorporating Senzing Entity Resolution into IMT Intel: ID. Senzing provides the first real-time AI for Entity Resolution. “IMT is a world leader in deploying entity resolution technology. We are very excited about the synergies between our companies” says Jeff Jonas, CEO of Senzing. Brian Eckhardt, CEO of IMT commented “We are very excited to partner with Senzing. Using Senzing technology, we can provide our clients with a tangible ROI and business benefit in weeks, not years”.
Integration to IBM i2 Analyst Notebook
Intel:ID now provides a plug-in for rich integration to IBM i2 Analyst Notebook, one of the leading analyst notebooks used in law enforcement today. With the new plugin, relationships of interest such as “Good Guy knows Bad Guy”, are highlighted in i2 Analyst Notebook. This allows investigators to focus on interesting persons more quickly. All relevant data is returned from all contributing sources to provide a complete dossier for the person. “The plugin also finds the path between two
individuals based on ‘new’ findings not otherwise apparent in incident reports where explicit relationships are already known” says Peter Huber, IMT’s Practice Lead for Justice, Threat and Fraud.
Natural Language Processing for Entity Extraction
With built in Natural Language Processing, Intel:ID crawls through large volumes of unstructured text reports, extracting key entities and relating them to person records. For example, when examining a person of interest, document segments referring to the person or related parties are shown with the ability to access the full document with a single click.
For more information contact Mark Holmes at email@example.com.