Chiwon Lee · CLIENT: Multitude Insights
Bltn is a Software as a Service (SaaS) platform that integrates Natural Language Processing Technology (NLP) and Artificial Intelligence (AI) to streamline public safety efforts in Government Technology (GovTech). Bltn simplifies data input and sharing for law enforcement officers, ensuring seamless operations. Its advanced search uses intricate algorithms for efficient case identification. The incorporation of AI enhances crime resolution speed and accuracy. Bltn's practical and functional design delivers straightforward solutions, making it a valuable asset for law enforcement agencies.
Press Kit
- Unique Properties
- BLTN is an AI-powered information-sharing platform for police officers. As officers upload crime data into BLTN, the AI looks for connections between them and intelligently alerts users. BLTN uses NLP and object recognition to look for clues that can unlock a case, especially for crimes that span multiple jurisdictions. Then, users connect through on-platform messaging and collaborative analysis tools. BLTN has successfully solved burglary, gang, and missing child cases across the U.S.
- Dimensions & Packaging
- Web dimensions are 1440 px * 1024 px. BLTN is a B2G SaaS product available on the Web and Mobile that is FBI CJIS certified. It is only available to licensed and authorized individuals in the law enforcement space.
- Tags
- Artificial Intelligence, Natural Language Processing, Public Safety, Collaboration, Information Sharing, Digital Infrastructure, Civic Technology, Crime Reduction
- Production Technology
- The platform is hosted on AWS and powered by NLP and AI. The NLP aids the search feature and the AI enables the recommendation and detection feature. An advanced Geographic Information System (GIS) technology is employed to enable the geo-visualization of crime data. The design was primarily carried out in Figma by using a design system and informed by quantitative and qualitative research with real users. The qualitative research was analyzed via open coding and affinity diagramming.
- Design Challenge
- The challenge is that BLTN is addressing a data heavy and complex space that requires advanced levels of security and visibility controls due to the nature of the law enforcement industry. BLTN also has a variety of features powered by advanced technology that need to be compatible with each other. It was challenging to ensure the data is easy to consume, easy to navigate, and easy to share while also applying technological advances to aid the users in the law enforcement space.
- Project Duration
- BLTN was published in May, 2022, and the design project for refining BLTN started in May, 2023 and finished in September, 2023 in the United States.
- Operation Flow
- Police users log in and can view posts from other users and agencies in their area. They can view these in a grid or geo-referenced manner. As officers post, an AI scans all media, text, and unstructured data for connections. Users are alerted to relevant links and put in contact with the relevant agencies/users via on-platform messaging. Users can link data through link controls and visualize linkages on the map or evidence board views helping to solve the crime.
- Research
- Qualitative research was conducted on law enforcement officers that are users of BLTN with the objective of understanding user pain points and user needs. Semi-structured interviews and task analysis was conducted via online conferencing tools. The research data was analyzed through open coding and affinity diagramming. The software version with user insights applied has been selected as the central communications platform for the High Intensity Drug Trafficking Area (HIDTA) program.
- Inspiration
- More than 50% of crimes in the United States remain unsolved. This is primarily because very few inter-agency data sharing initiatives exist, so criminals can easily move between jurisdictions. Further, it is difficult to upload and share data as existing platforms require manual entry. Because of these disconnected and manual systems, detecting trends and connections between crimes is an incredibly complex problem given the size and scope of data uploaded daily.
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