Cara Jones is the CEO and co-founder of Marinus Analytics, Cara is obsessed with high tech implementations that maximize the efficiency, and by extension, impact, of agencies. Her desire to serve the general public safety and human services sector was influenced by her father’s profession as a forensic social employee. She has managed the maturation and commercialization of Marinus Analytics’s Traffic Jam software for the reason that company’s founding. She has a deep wealth of experience starting from engineering autonomous robots, integration testing federal enterprise IT, and even coaching ice hockey, and leads Marinus’s expansion across law enforcement, government, and company sectors.
Marinus Analytics is a woman-owned AI company dedicated to advancing public safety by tackling human trafficking, child exploitation, and cyber fraud. Its powerful AI tools, like Traffic Jam and Cyber Fraud (developed with IBM Watson), help law enforcement discover criminal networks and save 1000’s of investigative hours. By analyzing public data from exploitation hotspots, Marinus empowers authorities with actionable insights—without compromising privacy.
Are you able to tell us more concerning the founding of Marinus Analytics and what inspired you and your co-founder to create AI solutions for public safety?
What inspired us then, and continues to encourage us daily, is to be in service to frontline public safety champions of victim-centered trauma-informed policing. I clearly remember the primary time I spoke with a federal agent who was looking for a missing and trafficked child, I knew it will be a joy to dedicate my profession to helping professionals who specialise in this field. We discover the motivation to support these agents, detectives, and analysts through our purposely built technology. Ultimately, credit is resulting from these unsung heroes who work tirelessly to guard the vulnerable from digitally enabled business sexual exploitation.
How did your background in robotics and AI research at Carnegie Mellon University influence the vision for Marinus Analytics?
The work on the Auton Lab (the research lab where Traffic Jam was conceived) has focused on social impact across different areas of presidency for over thirty years. These values are central to our work as we transitioned outside the university and have become a vendor to public sector clients.
My business perspective on lean innovation was gained during my early profession working for a robotics startup (which also got here out of Carnegie Mellon University.) Their revenue model, which was novel then, for pay-as-you-go leasing of the robots motivated us to operate Traffic Jam as a Software-as-a-Service. I even have all the time been interested in the democratization of technology through this model. It reduces the financial risk of becoming an early adopter of a non-mainstream solution. Thankfully, we received generous support from the National Science Foundation to subsidize the research and development and to permit us to supply access through an inexpensive subscription.
Why Pittsburgh? How has the town supported the event of Marinus Analytics? What resources and benefits are presented by being there?
AI began in Pittsburgh, with Carnegie Mellon University as a trailblazer for the reason that Fifties. Pittsburgh’s ecosystem includes over 100 firms focused on robotics and AI, with a workforce of seven,000+. It fosters cutting-edge advancements in AI solutions for public safety, transportation, healthcare, and far more, positioning itself as a frontrunner in artificial intelligence and automation.
Once I left for school, picking a significant in computer engineering almost necessarily meant I’d not return here to work. Due to the world-class AI programs at Carnegie Mellon University and its effect on the region’s economy, and to the Pittsburgh programs to support, fund, and mentor social entrepreneurs, I got to construct my dream job in my hometown. We now have recruited talented engineers from our local colleges, we built a sustainable business model with the recommendation of the Project Olympus campus incubator, and we got access to funding through UpPrize, Idea Foundry, and, most recently, the Richard King Mellon Foundation. We even have valued cheerleaders on the Pittsburgh Tech Council for innovation within the Pittsburgh region.
How has the corporate’s mission to combat human trafficking and exploitation evolved since its founding?
The mission has been consistent over time. We are going to proceed to innovate and promote victim-centered trauma-informed policing. What began here in Pittsburgh is now in use by public safety agencies across three continents, and this internationalization is expanding through our London office, which opened in 2023.
We support public safety agencies in countries where the laws and culture around business adult services vary significantly, however the commonality is to proactively address exploitation inside high-risk markets. We aim to proceed to spread best practices across the geographically diverse skilled community we serve, who’re united on this common goal.
What does the recent $400K investment from the Richard King Mellon Foundation mean for Marinus Analytics, and the way do you propose to make use of this funding to further your impact?
Receiving this investment from the Richard King Mellon Foundation is an incredible honor. This funding will allow us to expand our software for the advantage of child welfare organizations and broaden our positive impact on the fight against human trafficking and online harm. We’re proud to partner with the RK Mellon Foundation in our shared goal to proactively scale and protect our most vulnerable populations.
Your AI solution Traffic Jam has saved an estimated 70,000 investigative hours. Are you able to walk us through how the platform helps law enforcement discover victims of human trafficking more efficiently?
Traffic Jam uses AI and automation to attract connections between promoting on adult service web sites and missing person photos provided to law enforcement, where appearances are sometimes drastically altered. In this instance, AI can provide increased accuracy with greater efficiency than a human working manually. A victim could be rescued in days as a substitute of what may need been months.
The time of our frontline champions is so a lot better spent out locally serving people in need, forming relationships, and using their experience to proactively discover problematic situations. Their time could be wasted sitting at the pc, while automation can do this efficiently and accurately, freeing up a resource to make neighborhoods safer. It fundamentally helps them to change into more proactive.
What ethical considerations are in place when developing AI-driven tools for public safety, especially regarding privacy and data security?
After we speak about investigating business sexual exploitation, we start with the understanding it have to be handled with sensitivity. The moral considerations are what motivates our work. We diligently address data privacy and security measures during development and thru our client relationships to make sure the service we’re providing to police just isn’t only an ethical solution but the most effective tool to disrupt business exploitation.
In what ways has Marinus Analytics partnered with law enforcement agencies and social service organizations to directly assist victims of human trafficking?
Marinus Analytics partners with public safety agencies worldwide, and we’re excited to welcome a statewide child welfare agency as an early adopter of our technology on this critical space. With our MPWatch (Missing Individuals Watch) technology, they’re taking the lead in protecting at-risk children and locating missing minors. By collaborating with police and child welfare teams, we help ensure victims are identified quickly and resources are used efficiently. Our tools empower frontline professionals to act swiftly, making a direct impact within the fight to safeguard vulnerable individuals—just as we attempt to do with all our partners.
How does your AI help public safety professionals discover trends and patterns that will otherwise go unnoticed in human trafficking investigations?
Certainly one of the challenges in human trafficking prosecutions is an over-reliance on the victim to supply evidence against the trafficker. It’s an actual burden to put on a person who is commonly fearful for themselves and their members of the family. The technology can gather evidence and harness data to inform its own story of how exploitation occurred, identifying networks and trends that will point to organized crime. Without the help of purposely built technology, identifying those self same networks is probably not possible through a victim’s account or would otherwise take many more hours, dollars, and department resources. We hope this can be a game-changer for future cases.
What latest advancements in AI do you see on the horizon that would further enhance Marinus Analytics’ ability to disrupt human trafficking and arranged crime?
The rapid evolution of open-source multimodal AI models represents a major breakthrough in our fight against human trafficking. These advanced models are being trained on increasingly vast datasets, opening latest frontiers to use to our investigative capabilities. By leveraging these large-scale, open-source models, we will employ knowledge distillation techniques to create specialized, smaller models tailored to our specific use cases, using less training data than would otherwise be essential. This approach is especially precious given the sensitive nature of our work, where access to extensive training data could be limited. These distilled models maintain much of the aptitude of their larger counterparts while being more efficient and deployable in resource-constrained environments.
Moreover, these multimodal models are advancing our ability to generate more practical embeddings for each textual and visual data. This enhancement significantly improves information retrieval and cross-referencing capabilities, allowing us to discover patterns and connections which may otherwise remain hidden. As an illustration, we will more accurately match and cross-reference images and textual descriptions across various data sources, potentially uncovering criminal networks and trafficking operations more effectively. As these AI models proceed to evolve, we anticipate even greater advancements in our ability to process and analyze complex, multimodal data streams, ultimately enhancing our capability to disrupt criminal activities and protect vulnerable individuals.
