Fido

AI-assisted investigative intelligence

Fido

AI-assisted investigative intelligence

Fido

AI-assisted investigative intelligence

O V E R V I E W

FIDO is an AI-assisted investigative intelligence system that digitizes handwritten field notes and organizes case information through smart tagging, following a RAG-inspired interaction model.

M Y R O L E

User Research, Product Ideation, Concept Mapping, Information Architecture, IoT Ecosystem, Business Model, 3D Modeling + Rendering, Hi-Fi Prototyping

T E A M

Product Designer (me), UX Designer, Developer

I M P A C T

93.8 SUS, 92 NPS

D U R A T I O N

March 2025

2 Months

March 2025

2 Months

T O O L S

P R O B L E M S T A T E M E N T

How might we minimize paperwork for detectives, allowing them to focus more on on-site investigations and resolve cases faster?

I N T R O D U C I N G F I D O

We designed a pen that writes on paper digitizes notes in real time

It writes. It records. It learns. Powered by NLP and ML, it identifies key information, applies smart tags, and structures data for contextual retrieval.

U X R

How did we get here?

We started with Double Diamond research

And discovered

competitors were solving some other problems

Competitors offered complex, high-tech platforms -while we asked: what if detectives need a niche tool designed just for them?

U S E R J O U R N E Y

This niche approach meant we had to understand:

how do detectives actually work?

This niche approach meant we had to understand: how do detectives actually work?

K E Y I N S I G H T S

After four weeks of research and detective interviews

- here's what we found

Challenge 1

Critical Details Get Buried in Notes

Challenge 2

Investigations Are Hard to Capture in Real Time

Challenge 3

Reporting is Time-Consuming and Inconsistent

Challenge 4

Making Sense of Complex Case Data

I D E A T I O N

So we brainstormed:

how do we create real value for them?

So we brainstormed:

how do we create real value?

The Value Proposition Canvas helped us understand how the proposed tool creates value for detectives by addressing their tasks, challenges, and desired outcomes.

S T O R Y B O A R D

Before we continue

—a quick peek at Fido in action

Before we continue—a quick

peek at Fido in action

Before we continue——a quick

peek at Fido in action

P R O T O T Y P I N G

We thought:

what if their everyday pen became

their smartest partner?

We thought:

what if their everyday pen became

their smartest partner?

We thought:

what if their everyday pen became their smartest partner?

We noticed detectives carry a pen and notepad every day on the field—so we designed our idea around that habit

Developed through 65+ sketches across

30+ pages into one compact, versatile design.

Developed through 65+ sketches across

30+ pages into one compact, versatile design.

Developed through 65+ sketches across 30+ pages into one compact, versatile design.

We mapped the pen IoT ecosystem

to prove the concept worked

We mapped the pen IoT ecosystem

to prove the concept worked

We mapped the pen IoT ecosystem to prove the concept worked

Get High-res Ecosystem Blueprint here.

T E S T I N G

Next, we designed screens and testing

revealed two critical screens

Next, we designed screens and testing revealed two critical screens

/ / I S S U E # 1

Home Page

Users struggled to locate notes

Cluttered interface forced users to guess for information

Users wasted time searching for information instead of solving cases

Before

M Y A I W O R K F L O W

I reorganized the homepage around the core concept of digitizing notes—

displaying all case-related notes upfront so detectives see what

matters instantly instead of navigating buried tabs.

As note folders became the homepage focus,

we explored their design.

As note folders became the homepage focus, we explored their design.

Once folders were designed, we moved

to the pages within them.

U X I M P R O V E M E N T

100% of users easily found notes within case folders

85% users experienced smoother navigation through visual hierarchy

All important information was immediately accessible—no more searching

Before

After

/ / I S S U E # 2

Digitized Notes Page

Reviewing notes felt overwhelming due to long, text-heavy content.

Tags were hard to find and not clearly connected to specific parts of the notes.

Users had no dedicated way to review key information without distractions.

Before

M Y A I W O R K F L O W

I addressed this by using a combination of AI UX patterns and behavior-focused controls.

The three patterns — Immersive, Assistive, and Embedded — define where and how AI appears in the interface, while built-in AI behavior controls determine how the AI responds, guides, and supports the user.

U X I M P R O V E M E N T

I M P R O V E M E N T 1
Immersive Pattern
Pattern definition:
The interface focuses on one task, with AI guiding the user in a full-screen view.
What changed:
Handwritten notes were digitized and summarized into a full-screen view for focused review.
Solves:
Issue 1 (content overload)
Issue 3 (lack of focused review)
I M P R O V E M E N T 2
Assistive Pattern
Pattern definition:
AI provides guidance or context alongside the content without taking over the interface.
What changed:
Tags were made highly visible and connected to related evidence through a contextual side panel.
Solves:
Issue 2 (poor tag discoverability)
Issue 3 (lack of focused review)
I M P R O V E M E N T 3
Embedded Pattern
Pattern definition:
AI is integrated directly into content to offer subtle, in-place support.
What changed:
Users could refine bullet points or attach tags directly using right-click actions.
Solves:
Issue 1 (content overload)
Issue 3 (difficulty identifying key information)

I M P R O V E M E N T 1
Immersive Pattern
Pattern definition:
The interface focuses on one task, with AI guiding the user in a full-screen view.
What changed:
Handwritten notes were digitized and summarized into a full-screen view for focused review.
Solves:
Issue 1 (content overload)
Issue 3 (lack of focused review)
I M P R O V E M E N T 2
Assistive Pattern
Pattern definition:
AI provides guidance or context alongside the content without taking over the interface.
What changed:
Tags were made highly visible and connected to related evidence through a contextual side panel.
Solves:
Issue 2 (poor tag discoverability)
Issue 3 (lack of focused review)
I M P R O V E M E N T 3
Embedded Pattern
Pattern definition:
AI is integrated directly into content to offer subtle, in-place support.
What changed:
Users could refine bullet points or attach tags directly using right-click actions.
Solves:
Issue 1 (content overload)
Issue 3 (difficulty identifying key information)

R E S U L T S

Finally detectives approved

it for their workflow

Finally detectives approved

it for their workflow

You’re doing real problem-solving work here. The pen is a game-changer- a must-have solution.

Captain Roger Spurgeon

Homicide Commander @ IMPD

Captain Roger Spurgeon

Homicide Commander @ IMPD

/01

I love Dashboard’s well-structured, clear visual hierarchy, so nothing gets lost.

Eli McAlister

Lieutant @ IMPD

Eli McAlister

Lieutant @ IMPD

/02

The tags are a brilliant USP - it simplifies tasks immensely.

Killed it!

The tags are a brilliant USP - it simplifies tasks immensely.

Killed it!

The tags are a brilliant USP - it simplifies tasks immensely.

Killed it!

Ron Brumbarger

Founder - Team Monocles

Ron Brumbarger

Founder - Team Monocles

/03

Great Job !!

Love the idea of a new IoT device.

Great Job !!

Love the idea of a new IoT device.

Great Job !!

Love the idea of a new IoT device.

Terri Wada

Professor IoT Bussiness @ IU

Terri Wada

Professor IoT Bussiness @ IU

/04

F I N A L S O L U T I O N

Built for real detective work:

🕵🏽‍♂️ Fast, Smart, and Efficient

Built for real detective work:

🕵🏽‍♂️ Fast, Smart, and Efficient

C H A L L E N G E 1 / 4

How do we stop critical details

from getting buried?

How do we stop critical details from getting buried?

Designed a tagging system that surfaces critical evidence in context, keeping key details accessible and actionable.

Defined semantic tags for faster data retrieval and analysis:

Defined semantic tags for faster

data retrieval and analysis:

Defined semantic tags for faster

data retrieval and analysis:

Evidence Tag

Highlights key evidence

mentioned in notes.

Evidence Tag

Highlights key evidence

mentioned in notes.

Relation Tag

Flags potential suspects referenced in the notes.

Relation Tag

Flags potential suspects referenced in the notes.

Contradiction Tag

Identifies statements that

conflict with verified data.

Contradiction Tag

Identifies statements that

conflict with verified data.

Hypothesis Tag

Marks theories & show supporting confidence levels.

Hypothesis Tag

Marks theories & show confidence levels.

Create New Tag

Users can create and assign their own tags for tailored investigations.

Create New Tag

Users can create and assign their own

tags for tailored investigations.

C H A L L E N G E 2 / 4

How do we capture

investigations in real-time?

How do we capture

investigations in real-time?

Twist the mic head to record.

Audio is transcribed and organized into the sections shown below.

Twist the mic head to record.

Audio is transcribed and organized into sections.

Twist the mic head to record.

Audio is transcribed and organized into the sections shown below.

Content Segmentation

Emotional Mapping

Detects emotional tones in

the audio for better context.

Contradiction Detection

Flags statements inconsistent

with existing case data.

Related Files

Shows linked files when

contradictions are found.

Smart Pen transform Speech into investigative insights

C H A L L E N G E 3 / 4

How do we make report

writing effortless?

How do we make report

writing effortless?

How do we make report writing effortless?

By selecting a report format and sources,
AI synthesizes case data into structured
reports with speed and clarity.

By selecting a report format and sources, AI synthesizes case data into structured reports with speed and clarity.

C H A L L E N G E 4 / 4

How do we make sense of

complex, scattered data?

How do we make sense of

complex, scattered data?

How do we make sense of complex, scattered data?

Ask Fido enables natural language queries, leveraging a RAG-like approach to retrieve relevant case data and generate contextual insights across files and connections.

Starting a Conversation