The KSU Office of Research and Commercialization facilitated the transition of academic AI research into a functional tool for public safety operations. This move marked a significant milestone in how local government agencies address the complex intersection of law enforcement and mental health support services. For years, police departments across the country have struggled with the reality that officers are often the first responders to individuals experiencing acute psychological or emotional distress, yet they lack the tools to identify these cases systematically after the sirens fade. In regions like Cobb County and similar jurisdictions, the sheer volume of paperwork generated daily creates a massive information bottleneck. Thousands of incident reports are filed, many containing subtle indicators of behavioral health crises that manual reviews simply cannot catch. This systematic gap often leaves vulnerable citizens without the clinical follow-up they desperately need to avoid future contact with the justice system.
Leveraging Artificial Intelligence for Crisis Identification
“CaseFinder” stands as the culmination of more than six years of intensive academic inquiry led by Dominic Thomas, a Professor of Information Systems at Kennesaw State University. The software leverages sophisticated natural language processing algorithms specifically trained to parse the unstructured narrative text found in police incident reports and 911 dispatch transcripts. Unlike traditional database searches that rely on specific checkboxes or rigid codes, this AI platform reads between the lines to detect linguistic patterns and contextual clues that signal a mental health component. This capability is crucial because officers on the scene might not always explicitly flag an event as a behavioral health crisis, especially when dealing with high-stress situations or complex interpersonal conflicts. By processing this information at a speed and scale unattainable by human auditors, the platform ensures that no critical detail remains hidden within the vast digital archives of public safety records.
The operational impact of this technology focuses on the prioritization of resources for co-responder teams and mental health professionals who work alongside law enforcement. By generating a curated list of high-priority cases, the system allows clinicians to focus their outreach efforts on individuals most likely to benefit from immediate intervention and long-term care plans. This automated screening process removes the guesswork from the equation, transforming static documentation into a dynamic diagnostic asset for the entire community. The effectiveness of these algorithms is not merely theoretical; it is grounded in peer-reviewed research and has undergone extensive validation through real-world testing with various local agencies. This rigorous development cycle ensured that the tool could handle the specific vernacular and reporting styles unique to law enforcement, making it a reliable partner for departments looking to modernize their response strategies in 2026.
Facilitating the Transition from Lab to Field
The KSU Office of Research played an indispensable role in navigating the complex pathway from a university laboratory to the public sector market. Managing the intellectual property developed during the academic phase required a strategic approach to ensure the technology could be scaled effectively while maintaining its scientific integrity. The office conducted a comprehensive assessment of the platform’s market potential, ultimately structuring an exclusive commercialization license for Technovative AI. This arrangement allowed KSU to keep its researchers deeply involved in the ongoing evolution of the software while handing over the logistical and operational responsibilities to a dedicated private entity. By bridging this gap, the university demonstrated how modern higher education institutions can serve as engines of innovation that provide tangible benefits to their surrounding communities. This model of tech transfer ensures that high-impact research enters the real world.
Technovative AI brings a wealth of industrial and consulting expertise to the partnership, with a leadership team that draws from backgrounds at prestigious firms like McKinsey and Honeywell. This private-sector involvement is critical for deploying high-stakes software in environments where security, uptime, and data privacy are paramount. The company provides the technical infrastructure and support necessary to integrate the software into existing police workflows without disrupting daily operations. This collaboration highlights a growing trend where commercial partners take the lead on productization, allowing academic researchers to focus on refining the underlying logic and expanding the tool’s capabilities. The result is a robust, enterprise-grade platform that is ready for widespread adoption across diverse jurisdictions. The involvement of such experienced partners ensures that the transition to AI-driven public safety is handled with the professional rigor required by government agencies and their constituents.
Operational Success in the Moultrie Pilot Program
The Moultrie Police Department was selected as the primary site for the pilot program, serving as a vital proof-of-concept for the technology in a real-world setting. To facilitate this crucial testing phase, Technovative AI made the strategic decision to waive licensing fees, allowing the department to host the platform directly on its own internal hardware. This local deployment is essential for maintaining data sovereignty and ensuring that sensitive law enforcement records remain under the department’s direct control. In exchange for this access, the Moultrie Police Department provides structured, granular feedback that is used to refine the AI’s accuracy and user interface. This iterative process ensures that the software is tailored to the practical needs of officers in the field, rather than just the expectations of software developers. The success of this pilot hinges on this symbiotic relationship, where the department gains a cutting-edge tool while the developers gain the data needed to perfect their product.
A defining feature of the implementation in Moultrie is the active participation of the Georgia Pines Community Service Board, which provides the clinical backbone for the initiative. As a regional provider of behavioral health services, Georgia Pines supplies the professional co-responders who take action based on the data surfaced by the automated platform. This ensures that the information generated by the artificial intelligence leads directly to clinical care and social service support, rather than just sitting in a digital file. This partnership illustrates a significant shift in the state’s approach to public safety, moving toward a unified model that treats mental health crises as medical issues rather than purely criminal ones. By connecting law enforcement data with social service expertise, the pilot program creates a closed-loop system where individuals in distress are identified, evaluated, and directed toward appropriate treatment pathways, thereby improving the overall health of the entire community.
Developing a National Model for Community Safety
The philosophical shift underlying this project reflects a broader movement within modern law enforcement to become a primary conduit to the healthcare system. Moultrie Police Chief Chad Castleberry has emphasized that the “CaseFinder” platform allows his department to fulfill its ethical responsibility to the community at a scale that was previously physically impossible. By identifying individuals who might otherwise fall through the cracks of the system, the department is actively working to reduce the burden on local jails and emergency rooms. This proactive approach helps to de-escalate potential future conflicts by addressing the root causes of certain behaviors before they lead to serious criminal charges. The technology serves as a force multiplier, enhancing the efficiency of human experts rather than replacing them. This allows the department to deploy its limited personnel more effectively, ensuring that officers are available for traditional public safety duties while specialists handle the complexities of behavioral health.
The successful launch of the initial pilot established a foundational framework for how law enforcement agencies utilized “dark data”—the vast, untapped reservoirs of information buried within incident reports—to serve vulnerable populations. As the program moved into its full operational phase, administrators prioritized the expansion of the software to include predictive analytics that suggested when specific neighborhoods might require additional social service resources. Stakeholders recommended that other jurisdictions looking to replicate this success should focus on building strong relationships with local health boards before deploying the technology. This strategy ensured that the AI-generated insights always had a clear path toward clinical resolution. The collaboration between Kennesaw State University, Technovative AI, and the Moultrie Police Department ultimately demonstrated that the most effective way to modernize public safety was through a transparent, multi-disciplinary approach that valued community wellness as much as order.
