By Kaushal Bheda, Director at Pelorus Technologies
Forensics once meant fingerprints, footprints, and witness statements. Investigators depended on what people saw or remembered. Investigations moved at a slow pace. Today, every person leaves a digital trail via smart phones, smart watches, laptops, CCTVs, and connected cars. These digital devices are your new eyewitnesses. They quietly record where you go, what you do, who you talk to, and when you do it.
But this new world has brought in a new problem for the investigating officer, which is a deluge of data. Every phone now holds thousands of photos, years of messages, full app histories, and location logs down to the minute. Smartwatches record pulse data and sleep cycles. CCTVs capture hours of footage every day. One case can easily involve terabytes of information. What was supposed to help solve cases is now slowing the pace of solving them.
This is where artificial intelligence investigation tools step in. AI can scan data from phones, cameras, and computers together and pick out what looks unusual. It might notice a sudden message exchange at midnight, a missing location entry between two known stops, or a repeated face in different camera feeds. Instead of searching file by file and folder by folder, the system presents leads upfront.
AI also understands context. It can piece together how different actions link to each other. For example, it can match a photo taken on a phone with the exact location and time it was shot, then connect that to a call or message sent at that same moment. It can spot that a file shared over email is the same one later uploaded to a cloud drive or forwarded in a chat. If someone deletes a message and turns off their phone right after meeting another suspect, AI can line up those events and flag the sequence as suspicious. By linking these small clues, it builds a complete timeline that a human officer would struggle to see manually.
Another big change is how officers interact with these systems. They no longer need to know complex commands or multiple systems. They can just type or speak naturally, such as “show all calls around the time of the break-in” or “find videos where both these people appear.” The system interprets the request and produces the right results.
AI is also reshaping how evidence is presented and reviewed. In the past, investigators created manual timelines and visual charts. Now, AI systems automatically generate timelines, highlight key digital events, and create clear visual links between suspects, devices, and actions. This makes it easier to explain cases to courts and juries, especially in complex cyber investigations where raw data can run into millions of records.
For investigating officers in India and elsewhere, this shift is both a relief and a challenge. AI shortens case time and helps manage the flood of data. But every AI-driven result still needs verification. Evidence must be explainable in court and traceable to its source.
The future of investigation is ingesting all the investigation-related data into an AI system, sipping a cup of chai, reviewing the results and verifying that the suspects and insights match the underlying data, and having a perfect report submitted in court without errors or hallucinations. Ingest, review, submit, repeat.