What 30 Days of AI Casework Looked Like in One Police Department

Back to all articles

A detective in one police department had about 2,000 pages of Instagram warrant returns sitting in front of him in a stolen handgun case. His estimate for reviewing it by hand was simple, weeks. Using an AI casework tool, he got through it in about 20 minutes and surfaced messages that pointed to who likely had the gun.

That is the kind of result command staff should pay attention to, not because it sounds flashy, but because it gets at a very real problem inside investigations right now. Digital evidence is piling up faster than detectives can reasonably read it. Phone extractions, social media returns, documents, jail calls, bodycam, interview video, bank records. None of it is getting smaller. And the cost is not just overtime or frustration. The real cost is that leads sit buried while investigators scroll, skim, and try not to miss something important.

In this department's first 30 days using an AI casework platform, detectives did not treat it like a novelty. They used it across eight active investigations, including a stolen firearm case, multiple fraud cases, a fraud-and-forgery series, and a harassment case involving a firearm threat. Detectives across the unit had logins and used the tool, not just one motivated early adopter. That matters, because the real test of any investigative software is whether a full unit actually works it into the day.

It started with speed, but speed was not the whole story

The 2,000-page Instagram return is the headline example for a reason. Every detective knows what that kind of data dump feels like. You start reading, then searching, then opening attachments, then trying to build a timeline in your head while hoping the key exchange is not sitting on page 1,347. In this case, the tool cut the first-pass review from weeks to minutes and helped surface a lead tied to possession of the gun. The detective later described the result as amazing, mainly because he knew exactly how long that same task would have taken by hand.

That same pattern showed up in other cases. On one investigation, more than 150 separate evidence items were loaded and analyzed at once. Instead of forcing the detective to open each piece individually and mentally stitch everything together, the tool let him ask plain-English questions across the full evidence set. That means a detective can ask what links a suspect to a location, what witnesses mention a firearm, whether there are timeline gaps, or what records appear to contradict a statement, and get pointed back to the underlying material fast.

This is where AI starts to matter in casework. Not as a substitute for investigative judgment, and not as a black box making decisions for the detective. It matters because it handles the first layer of grind work at machine speed, across more material than a person can comfortably hold in working memory. The detective still decides what matters. The tool helps surface it before the trail gets cold.

Where the unit actually used it in the first 30 days

The department did not keep the tool boxed into one narrow task. Detectives used it across the normal rhythm of investigations, from intake to reports to legal review.

Evidence review and question answering

This was the most obvious win. Detectives uploaded full evidence sets, including phone extractions, warrant returns, documents, and video interviews, then asked direct questions in plain English. They used it to generate case summaries, identify leads, and get next-step recommendations. They also used it to build practical to-do lists, what still needed independent verification, which witnesses still needed statements, and what records should be requested next.

That kind of help is useful because good investigations are not just about finding one answer. They are about keeping a clean list of what is known, what is not known, and what needs to happen next.

Drafting search warrants and reports

Detectives also used the tool to draft search warrants, including probable cause statements and items to be seized, in their own paragraph style. That point is worth slowing down on. Investigators do not want software that spits out canned language that sounds nothing like them and creates more editing work than it saves. In this rollout, the tool was used to produce drafts that matched the detective's own writing style closely enough to be useful.

It also helped tighten probable cause language. One investigator used it to condense what he described as fluffy PC statements into something more focused and readable. That is not a cosmetic improvement. Cleaner writing helps supervisors, prosecutors, and judges understand the basis for the request faster, which can reduce friction and improve the quality of the paper going out the door.

The same applied to report writing. Detectives used the tool to turn bodycam footage and recorded interviews into written reports, then refine those drafts as needed. Again, the point is not to remove the detective from the process. The point is to get from raw media to a working draft without burning hours on transcription and summary work.

Legal defensibility and warrant scope

One of the more important use cases had nothing to do with speed. It had to do with getting the legal scope right. In one example, a reviewing attorney flagged a cell-phone warrant as potentially over-broad. Using the tool, the detective tightened the request by limiting parameters and narrowing the timeline to 45 days.

That is the kind of practical support command staff should care about. Better technology should not just help move faster. It should help teams make cleaner, more defensible decisions. Investigators also used the tool to think through scope questions in the other direction, such as whether a warrant timeline should be broader in a case involving a firearm threat. That is useful because the tool can help frame the issue, organize the facts, and point back to the evidence, while the detective and reviewing attorney make the actual call.

Interview prep

Another smart use was interview prep. Detectives asked questions like, Did I miss anything during my interview of the suspect? That is a good example of AI being used as a second set of eyes, not as a decision-maker. In a busy unit, detectives are often moving between calls, reports, subpoenas, victim contact, and case follow-up. A tool that helps flag missed threads before the next interview can improve the quality of the investigation without adding another hour of manual review.

What command staff should take from the first 30 days

The strongest signal from this rollout was not one dramatic result. It was repeated use by the unit across real cases. Eight active investigations in 30 days. Detectives across the whole unit using their own logins. More than 150 pieces of evidence analyzed at once on one case. A major social media return reduced from weeks of manual review to 20 minutes. That is not a canned demo. That is operational use.

There is also a capacity and wellness angle here that should not be ignored. A lot of investigative work now means long hours in front of screens, clicking through repetitive material and, in some cases, repeated exposure to disturbing content. If a tool can reduce the amount of manual review needed to find the useful parts, that is not just a productivity gain. It gives detectives more time for the work only they can do, interviews, strategy, corroboration, judgment calls, and victim or witness follow-up. It can also reduce some of the mental drain that comes from endless digital sorting.

The department also saw something else that matters when evaluating vendors. The rollout was hands-on. Detectives got same-day answers to questions. Issues were addressed quickly. At least one feature request from an investigator, saved per-user report preferences, went directly onto the product roadmap. According to a deputy chief's description, the tool was effectively selling itself internally because the detectives kept talking about it. That kind of buy-in usually comes from one thing, the product is helping on real work.

For a command staff member reading this, the takeaway is straightforward. If AI is going to earn a place in investigations, it has to do more than summarize files. It has to move cases faster, give detectives back time, support cleaner warrant work, and fit the way a real unit already operates. It should help teams handle growing evidence volume without assuming headcount will grow with it. And it should come with a vendor that listens closely enough to make product changes based on what investigators actually need.

Concrete takeaway: when you evaluate AI for casework, ask one hard question, does it reduce time to useful lead, improve the quality of warrants and reports, and get used across the unit after the demo is over. In this department's first 30 days, the answer was yes.

Disclaimer: The department and individuals described here are anonymized real users of the product. Specific identities and locations have been withheld.