A new artificial intelligence tool, Longeye, is being introduced into law enforcement and private investigtions as a more controlled and supposedly reliable alternative to the broader wave of AI systems that many people distrust. Detective Lauren Cunningham of the Oklahoma City Police Department began as a skeptic because she had already seen AI create confusion, misinformation, and harmful errors in other settings. But after testing Longeye, she found it useful because it was designed specifically for investigative work and limited to the evidence detectives themselves uploaded.
According to Longeye supporters, Longeye has already helped detectives save major amounts of time. Tasks that once took Cunningham roughly 20 hours each week, such as monitoring jail calls from murder suspects, were reduced to fewer than five hours. Other investigators used it to review thousands of pages of financial records more quickly, and one sex crimes investigator used it to translate suspect phone calls, uncovering a confession that may shift a child rape case from trial toward a plea agreement.
The company behind Longeye presents the system as an ethical AI platform that can help all sides of the criminal legal system, including police, prosecutors, defense lawyers, and corrections officials. Its founder, Guillaume Delépine, argues that many current law-enforcement AI tools are rushed, unreliable, or constitutionally questionable. He says Longeye was built differently, as a system focused on careful analysis rather than the “quick and dirty” methods that can create serious risks in criminal cases.
A key feature of Longeye is that it operates inside a “closed sandbox.” This means it does not pull information from the open internet or outside sources that could distort the analysis. Instead, it works only from case materials uploaded by investigators, such as documents, audio, video, and data obtained through legal process. The article suggests that this design is intended to reduce hallucinations, contamination, and the kinds of errors associated with public AI chatbots.
Even with these safeguards, the article stresses that AI in law enforcement remains controversial. Defense lawyers often challenge AI-assisted evidence as unreliable, jurors may distrust it, and courts still have not clearly decided when prosecutors must reveal that AI helped analyze evidence or contributed to conclusions in a case. Former Florida state’s attorney Aramis Ayala warns that justice is not automatically improved by new technology and that truth in the legal system depends on accuracy, not novelty.
Delépine claims the tool is already making a major impact. He says that in 2026 alone Longeye has condensed what would have been about 34 years of detective labor into only a few months of work, processing 25 million files across 35 agencies at the local, state, and federal levels. Still, the article points out that most of these cases have not yet been tested in court, so the long-term legal value and admissibility of Longeye’s work remain uncertain.
The article also explains why investigators may be drawn to a tool like this. Real investigative work is often less about dramatic arrests and more about sorting through massive amounts of digital evidence, interview recordings, and document dumps. Longeye can organize case information into timelines, maps, and spreadsheets, while also linking each conclusion back to its original source. It also maintains audit trails and follows FBI-style data security and privacy protocols, which could make it more useful in preserving chain of custody for court.
Another important theme in the article is fairness. Delépine says he wants Longeye to be available not just to police and prosecutors but also to public defenders and innocence organizations. Criminal defense investigator Marc Caudel believes AI could help narrow the resource gap between prosecution and defense by handling time-consuming review work, much like an assistant or intern. In that sense, AI might potentially make the justice system more balanced rather than simply more powerful for the state.
At the same time, the article highlights unresolved legal and policy questions. Courts have not fully addressed how AI affects Brady disclosure obligations, confrontation rights under the Sixth Amendment, and the need for a real person to explain and defend AI-generated findings in court. Experts argue that because lawyers cannot cross-examine a machine, a human investigator must be able to independently verify the AI’s analysis before relying on it in testimony or charging decisions.
Finally, the article places Longeye within a broader national debate over how police should use AI. Some states, like Utah and California, already require disclosure when generative AI is used in police report writing, while model legislation from groups like the Policing Project and the Electronic Frontier Foundation would impose stronger transparency rules. Meanwhile, agencies in Oklahoma and elsewhere are expanding tests of Longeye for policing and corrections, with supporters saying it helps analyze prison phone calls and confiscated cellphones more efficiently. The article ends by showing the central tension: AI may make investigations faster and more manageable, but whether it truly advances justice will depend on accuracy, transparency, and how the courts eventually respond.