Opinion
Don’t wait for the final episode: From solving crimes to preventing the next one in the AI era
In the AI era, the test is not only to connect the dots, but to do so in time to deliver justice and safety.
At the heart of a mysterious murder case in Boston, a father is accused of murdering his son. Thousands of miles away, in Switzerland, a child from a local orphanage disappears without a trace. Seemingly, these are two completely separate cases, taking place in different countries with no connection between them. But then comes the twist (spoiler alert): cross-referencing the investigative findings through Interpol reveals that the two cases are connected and that the same person is behind them.
This fictional scenario, which lies at the heart of I Will Find You, Harlan Coben’s thriller series that held the No. 1 spot on Netflix for five consecutive weeks with more than 101 million views, raises a question that is increasingly relevant in real-world investigations: In an era in which almost every crime leaves behind vast amounts of digital traces, how can AI help investigators connect the dots early on - not only to understand the full picture of a crime that has already occurred, but also to prevent the next one?
You would be hard-pressed to find a crime today that does not leave a digital trail - messages, photos, location data, social media activity, and information from devices and the cloud. According to Cellebrite’s 2026 Global Industry Trends Report, 95% of investigators believe that digital evidence improves their ability to solve cases, while 94% say that the volume and complexity of information increase the investigative workload. In other words, precisely when the information available to investigators is richer than ever, it is becoming more difficult to identify the meaningful details and connections in time.
This is where AI enters the picture. Not as a replacement for the investigator, nor as an autonomous system that makes decisions on their behalf, but as a capability that can rapidly cross-reference information from different sources, identify patterns, detect anomalies, and surface connections that are almost impossible to detect for a human investigator working manually.
Consider, for example, an investigation into a rape. It may begin with the testimony of one victim and the phone of one suspect, but the analysis of digital information may reveal a recurring pattern and lead to additional victims who never filed a complaint. The same is true of a drug investigation: what begins with suspicion surrounding a single courier may lead to the exposure of an entire network - from the people directing the courier to the distribution network.
A breakthrough in an investigation does not always lie in what the investigator is looking for, but in what they do not yet know they should be looking for. This is the difference between solving a crime that has already occurred and solving a crime that has yet to occur, while there is still time to prevent it.
Revealing those patterns and connections can potentially help disrupt criminal activities at scale, optimize public safety agencies’ operations and foster collaboration between agencies as criminal rings and organizations often span multiple jurisdictions.
And this shift from response to prevention is already taking place in other fields. In finance, AI systems identify fraud patterns before the next fraud attempt; in cybersecurity, they connect different signals to identify an emerging attack; and in medicine, models help identify patient deterioration before it develops into a crisis. The world of investigations is now undergoing the same shift.
To move from solving crimes to preventing them, investigative tools must change as well. AI-powered investigative platforms allow investigators to ask complex questions and uncover connections that were not previously known. For example, an investigator might ask: “Based on everything we know right now, where could the next offense occur?”. In the past, answering such a question might have required weeks or even months of cross-referencing evidence. But in an investigation, and especially with time-sensitive cases, investigators often do not even have days to invest. By the time all the dots are connected, the next crime may already have occurred. With a purpose-built Agentic AI solution for investigations, Cellebrite Genesis, investigators can rapidly cross-reference and surface new insights in minutes, helping to identify and understand the critical information needed to act in time.
And that may be the biggest difference between a thriller series and a real-world investigation. With Harlan Coben, we can wait until the final episode to discover the full picture. Investigators do not have that luxury - and victims certainly do not. In the AI era, the test is not only to connect the dots, but to do so in time to deliver justice and safety. Because when the full picture emerges early enough, it can not only help solve the crime that has already occurred - but perhaps prevent the next episode.
The author is Evyatar Ramot, VP, Head of Innovation Center at Cellebrite.
