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C3 AI Intelligence Analysis

C3 AI Intelligence Analysis unifies disparate data sources and provides AI-driven insights and alerts that unveil relevant relationships and drive timely interventions.


Threats to states and local communities alike have become increasingly complex and difficult to mitigate with threat networks’ sophistication. To gain insights into elaborate networks, intelligence and law enforcement agencies are using AI and machine learning to gain visibility into threats, infer conclusions about complex networks, and make recommendations to optimize interventions.

At C3 AI, I designed a AI-powered intelligence product derived from research across intelligence and law enforcement agencies that reveals hidden connections within threat networks and provides intervention recommendations. The solution was imagined through intensive discovery workshops across intelligence use-cases and synthesized into a generic user experience applicable to different agency scales. 


Role: Sole UX Designer

Duration: 1 year


The content in this project is confidential in nature–specifics have been purposefully omitted. Please reach out if you would like to further discuss my process as the UX designer in imagining and delivering a successfully implemented solution.

The Value of AI-Driven Intelligence

Intelligence analysts operate in a constant state of needing to draw impactful conclusions based off very little information. Armed with disparate data sources with bulky UIs, their job becomes increasingly more difficult with constantly enhanced threat behavior sophistication. Below outlines a series of pain points shared across law enforcement and national intelligence with associated AI solutions.

Pain Points

Disparate intelligence data sources slow down access and preclude ability to draw holistic conclusions.
Intermittent data streams do not provide up-to-date operational picture.
Important decisions are made based on sparse data or “gut feelings” which lead to inaccurate conclusions and explainability issues.
Primitive visualizations used to reflect multi-dimensional, complex information obfuscate important insights.
Inefficient and disconnected case mechanisms make collaboration inefficient.

Associated AI Solutions

Unified, federated data image ingests data from multiple feeds, including structured and unstructured sources.
Near real-time data parsing extract entities and meaning from data – including people, places, activities and relationships.
AI-generated insights unearth patterns in complex data to complement user decision-making.
Interactive graph visualization and exploration capabilities make it easy to track entities and relationships.
Data and scenario versioning enhances collaboration between users allowing hypothesis exploration and custom storyboard creation.

Research Methodology & Personas

3 User Discovery Workshops

10+ Iterative User Testing Sessions

2 Detective Ride-Along Sessions

3 Organizations

4 Distinct Persona Roles

Crime Analyst

Monitors, analyzes, and presents crime trend findings within assigned jurisdiction.  


Gathers information regarding crime incidents and investigates patterns to produce justification for intervention.

Intelligence Analyst

Investigates threat networks and correlates patterns across individuals and assets to support investigative reports leading to intervention.

Chief Intelligence Analyst

Assigns work across intelligence analysts and presents threat trends and intervention progress.

Intelligence Analysis Demonstrated Benefits


Connect to any number of data sources


Automate data ingestion, cleaning, and adjudication


Explore multiple data sources from a unified view


Connect to any number of data sources