CASE STUDY | MULTI-SUSPECT INVESTIGATION | NOV 23, 2025
FLASH PD // INVESTIGATIVE INTELLIGENCE
How Whitehall PD Used AI to Accelerate a Multi-Suspect Shooting Investigation
Whitehall Police Department, Division of Police
AT A GLANCE
Case Summary
By the Numbers
2
TEENAGE GUNSHOT VICTIMS
50 to 70
SHELL CASINGS RECOVERED
14
TOTAL ARRESTS MADE
Days to hours
REVIEW TIME COMPRESSED
100%
SHOOTERS IDENTIFIED
Multi-cal.
EVIDENCE RECOVERED
THE CHALLENGE
The Challenge Was Not a Lack of Evidence. It Was the Volume of It.
When a case involves multiple shooters, multiple witnesses, and widespread chaos at the scene, investigators are immediately faced with competing accounts, evolving timelines, and an urgent need to identify who did what and why.
In the Whitehall case, detectives had hours of witness interview video that needed to be reviewed quickly and carefully. Under a traditional workflow, that kind of review would have required days of watching, note-taking, cross-referencing, and manually connecting statements across interviews.
At the same time, speed mattered. Public reporting described a shooting scene involving multiple masked individuals, two teenage victims, and dozens of shell casings recovered. In a case like that, every hour spent manually digging through interviews is time not spent acting on the leads those interviews contain.
The question was not whether the evidence was there. The question was how fast investigators could make it usable.
INVESTIGATION TIMELINE
From Scene to Arrests
NOV 23, 2025 ~4:00 AM
INCIDENT
A chaotic shooting scene created immediate investigative pressure.
INVESTIGATION BEGINS
EVIDENCE BURDEN
The evidence burden quickly shifted to witness interviews.
FLASH AI DEPLOYED
REVIEW COMPRESSED
Flash helped compress review time across hours of footage.
CASE OUTCOME
14 ARRESTS
The investigation moved toward 14 arrests.
“In a case like this, time matters. Flash helped us work through hours of interview footage much faster, compare statements more efficiently, and focus on the information that actually moved the investigation.”
DETECTIVE JASON KUBINSKI, WHITEHALL DIVISION OF POLICE
THE WORK
How the Investigation Unfolded
Multiple masked individuals were in the parking lot near a wedding reception in the 170 block of South Hamilton Road as the reception was ending. According to court documents cited in public reporting, the group fired guns first into the air and then into a crowd and nearby vehicles. Two 16-year-old girls were shot, and one of the victims was later struck by a car during the chaos. Detectives recovered approximately 50 to 70 shell casings of varying calibers from the scene.
As detectives worked the case, they gathered extensive witness interview video. The challenge was not simply to watch the footage. The challenge was to extract what mattered: names, relationships, timelines, motive indicators, inconsistencies, and details that could help identify each shooter and explain what drove the violence.
Using Flash AI, detectives were able to review and analyze hours of witness interview video far faster than a manual process would have allowed. Instead of relying exclusively on traditional interview review methods, investigators were able to move more quickly through the footage, compare statements, and focus on the details most likely to move the case forward.
That accelerated review helped detectives identify the identity and motive of all shooters, supporting a case that ultimately led to 14 arrests.
WHERE FLASH HELPED
Where Flash Made the Difference
Reduced review time
Cut review of hours of witness interview video down significantly.
Surfaced relevant statements faster
Helped detectives find what mattered in less time.
Made cross-referencing easier
Compared information across multiple interviews efficiently.
Accelerated path to leads
Supported a faster path from interview footage to actionable leads.
Reduced manual burden
Eased review work in a complex, high-pressure case.
Helped identify shooters and motive
Detectives identified the identity and motive of all shooters.
In this case, Flash did not replace detective work. It helped detectives get through the review burden faster so they could spend more time acting on what the interviews revealed.
OPERATIONAL IMPACT
Why This Matters for Agencies
This case is a strong example of where AI can create real value in law enforcement. Not by replacing investigators, but by helping them manage overwhelming review burdens in time-sensitive cases.
In a multi-suspect shooting investigation, speed matters. So does consistency. When detectives are working through hours of witness interview video, every hour spent manually rewinding, note-taking, and trying to connect statements is time not spent pursuing leads, preparing arrests, or advancing the case. Flash helped compress that review cycle and turn recorded interviews into usable investigative intelligence faster. For agencies facing larger and more complex case volumes, the lesson is simple: the bottleneck is often not access to evidence. It is the time required to make that evidence usable.
REVIEW SPEED
A review process that would normally have taken days was reduced to hours.
EFFICIENCY
Detectives were able to move faster through a large volume of witness interview video.
INTELLIGENCE
Investigators spent less time manually sorting footage and more time working the case.
CASE RESOLUTION
Detectives were able to identify the identity and motive of all shooters more quickly than manual review alone would have allowed.
BOTTOM LINE
Whitehall Detectives Did Not Need More Evidence. They Needed a Faster Way to Work Through It.
In this case, Flash helped detectives turn hours of witness interview video into something they could work with in real time, helping move a complex shooting investigation toward identifying the identity and motive of all shooters and making 14 arrests faster than traditional review alone would have allowed.
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