Sample Serve · capstone · 2026
Sample CSI
Digitizing crime scene evidence collection and documentation
TEAM
Reet O.
Simranpreet K.
Amulya V.
Tiffany
Cathy S.
ROLE
Product Designer
TIMELINE
Jan'26 -May'26
PROJECT TYPE
Internship
SKILLS
Interviews
Artifact study
Competitive analysis
AI Assisted Prototyping
Usability testing
ORGANISATION
Evidence Linking
Primary and secondary relationships
DATA ENTRY
Guided Capture
Required fields and AI prompts
RECORDS
Chain of Custody
Starts at the scene
SECURITY
Verified Handoff
Face ID before print and submit
01 · PROBLEM
Crime scenes are
chaotic
, but evidence records need to
be precise because one missing detail can cost
justice
Officers often collect evidence in stressful, time-sensitive environments, but the documentation process still relies on handwritten forms, manual entry, and disconnected systems. That creates room for missing details, illegible notes, duplicate work, and chain-of-custody gaps.
In the example below, OJ Simpson was going to get arrested for the murder of his ex-wife and her friend. However, the because of issues in evidence handling and documentation, the defense was able to build a case to plan sufficient doubt in the jury's head.
03 · ABOUT THE CLIENT
SampleServe had the foundation in
environemental evidence collection
SampleServe had already built tools for field-based sample collection. We explored how that same foundation could evolve into a crime scene workflow, helping officers document, label, link, and hand off evidence more reliably.
Before designing, we had to understand the
real process
04 · competitive analysis
Most tools managed evidence
after
it entered
the system
We analyzed Axon, Omnigo, and NICE to understand how existing platforms support evidence management. This helped us identify where tools were already strong, and where scene-side evidence capture was still underserved.
Takeaways:
1
Capture-Time Intelligence
Catch missing fields, invalid entries, and inconsistencies while evidence is being collected.
2
Crime-Scene first Design
Support the realities of fieldwork: multiple collectors, duplicate prevention, offline use, gloves, and high-stress conditions.
3
Prosecutor-Ready by Default
Structure evidence so it is easier to review, charge, and defend later, with fewer gaps and less back-and-forth.
04 · artifact study
The forms repeated the basics, but the
details
kept changing
We studied existing evidence forms to understand what information officers were expected to capture across different evidence types. This helped us define design requirements for a dynamic form system, where repeated fields could be auto-filled and evidence-specific fields could appear only when relevant.
04 · interviews
Interviewed 6 officers to understand evidence
collection from
field
to the
courtroom
We interviewed 6 law enforcement professionals to understand how evidence is collected, documented, handed off, and later defended in real workflows. The goal was to learn where officers lose time, rely on memory, or work around the current process.
1
04 · research insights
Officers would input data
again
and
again
and
again
LLMs pulled readers away while programmatic ads eroded the trust publishers had spent years building.
Redundant & Repetitive Work
“By the time you write it on the paper, write it in your notebook. Take the picture. Go back to the station. Put all of that stuff in the management system,” -PA
Inconsistent Documentation
“Your notes are only as good as the person writing them” - PA
Weak Chain of Custody
“If you skip any of those steps, it can kind of make the chain of custody a little bit muddled.” -PS
2
04 · research insights
Teams collaborate but the
systems don't
In addition, we also found a major disconnect between officers’ workflows and paper documentation. Paper is a rigid, 'solo' medium—but in reality, evidence collection is a collaborative team effort.
Chain of Custody Integrity
“By the time you write it on the paper, write it in your notebook. Take the picture. Go back to the station. Put all of that stuff in the management system,” -PA
Many roles dealing with the same scene
“What will have happen is… they forget to tell somebody or whatever else, and now that piece of paper sits somewhere on a desk or in a folder.” - PA
Communication with the records management system
“I go in and retype almost everything.” - PR
3
04 · research insights
Too much to think
thorugh, all at once
Crime scenes are high-pressure environments where limited mental bandwidth makes documentation a logistical burden, creating three primary risks:
Redundant & Repetitive Work
“By the time you write it on the paper, write it in your notebook. Take the picture. Go back to the station. Put all of that stuff in the management system,” -PA
Redundant & Repetitive Work
“By the time you write it on the paper, write it in your notebook. Take the picture. Go back to the station. Put all of that stuff in the management system,” -PA
Risk of Contamination & Mishandling
“I gotta put on a glove or I gotta take my gloves off. And now go and pick up this other thing.” - PA
After understanding the real needs, pain points
and processes, we mapped out
product direction
06 · DESIGN REQUIREMENTS
speed
accuracy and accountability
From research, we translated officer needs into clear product requirements.
The system needed to work quickly in the field, reduce manual errors, and keep every evidence action traceable.
These requirements helped us define the direction for the product experience.
07 · explorations
The team sketched multiple ways officers could move through the evidence collection process.
Each exploration brought a different perspective on navigation, evidence entry, review, and handoff.
This helped us move away from a linear form-based flow and toward a more flexible system.
Once we finalized the user flow, we designed and
built v1 prototype using AI assisted workflows
07 · usability test
Observed what users did, what they said, and
where the workflow slowed down.
We looked at the test from multiple angles, not just whether users completed the task. We tracked repeated behaviors, captured participant quotes, and measured flow-level friction. Together, this helped us understand both the visible and invisible parts of the experience.
07 · usability test insights
Officers showed us where the product needed
more clarity.
Testing revealed moments where labels, hierarchy, and evidence relationships were not clear enough. We used these insights to refine the dashboard, evidence capture, mapping, and chain-of-custody flows. The goal was to make the system easier to understand in high-pressure field conditions.
Home
“The cards can show the numbers of evidences involved in current cases.” -P4
We updated the home/dashboard to improve quick situational awareness.
Added evidence count to case cards (e.g., “Evidence (5)”)
Updated status labels to “Ongoing” and “Handed-off”
Evidence Collection Capture
“Since it will be a two person thing, the note taker should be able to say other person collected the evidence” -P3
We added fields like “Found By” and “Tests Conducted in the Field” to better align with real workflows.
Terminology was also refined by renaming "Requested Exams" to "Lab Exams" and simplifying unclear labels.
Lab exam options are now dynamically driven by the selected evidence type, reducing irrelevant choices and speeding up input.
Evidence Mapping
“Why am I linking it as a child? I am not aware of that terminology” -P3
We refined the evidence linking flow to better match how officers group related items.
Users now define one Primary item and assign multiple Secondary items in a single step, reducing repeated actions.
Terminology was updated from Parent/Child to Primary/Secondary, and evidence numbering now updates dynamically (e.g., PrimaryID-A) to clearly reflect relationships.
Evidence Mapping
“Is there a place where we could click and it would say where it was submitted to? Like submitted to state lab, or stored outside of evidence locker” -P2
Renamed “Activity Log” to “Chain of Custody” for clarity.
Entries are now more explicit and action-based, with an improved layout, highlighted updates, and clickable rows for detailed views.
Additional context, such as where evidence was submitted, improves traceability.
After the Usability Test Analysis, we implemented the changes
and handed off to the client
07 · Final Product
The final product turns a fragmented evidence
process into
one connected workflow
07 · Final Product
We shaped the product around three priorities:
speed, clarity, and traceability.
Every design decision was tied back to what officers needed during evidence collection.
We simplified repeated actions, made evidence relationships easier to understand, and added clearer status updates.
These decisions helped the product feel faster, more reliable, and easier to trust.
08 · Learning
My biggest learning was knowing
where AI
helps,
and where
human judgement matters
AI was most helpful when the task was repetitive, technical, or execution-heavy. We used it to create documents, support scripting, and build interactive HTML prototypes, which helped us move faster and test ideas more tangibly.
But we were careful not to use AI as the decision-maker. Research synthesis, usability insights, and product direction still needed researcher judgment, team discussion, and context from the field.
This taught me to use AI mindfully: not to replace thinking, but to reduce busywork and create more space for better design decisions.
