Event intelligence / product design
Signal clarity before the daily deadline.
Because this project is under NDA, this portfolio version shows the problem, workflow, design approach, high-level architecture and measurable impact using sanitized language, abstracted diagrams and generalized examples.
Daily intelligence brief
Evidence reviewed. Claims checked. Ready for editorial approval.
Role and context
Designed at JOJA as confidential product work.
I worked as the product strategist and designer, turning a manual intelligence workflow into a structured product concept for collecting event signals, evaluating evidence and producing a credible daily brief.
I do not show production screenshots, proprietary source lists, prompts, real outputs, internal data, client-specific details or implementation internals. The case study focuses on my role, process, workflow decisions and approved impact.
Company name is safe to show as workplace context.
Defined the use case, workflow, information architecture and product narrative.
From problem framing through product experience and case-study structure.
Reduced the average time needed to review signals, connect evidence and draw insights.
Concept flow
From scattered signals to a reviewed daily brief.
The case centers on one repeatable job: help a strategy team understand what matters during a live program, explain why it matters and publish a source-backed brief before the daily deadline.
Session transcript answer flow
The public version of the transcript Q&A logic shown in Carbon system styling.
End-to-end product flow
The safe public version of the product logic.
Daily operating loop
The repeated rhythm behind the time savings.
Problem
The work was not finding information. It was making sense of it fast.
During a live program, meaningful signals appear across schedules, sessions, social commentary, announcements, media coverage and internal observations. The team needed a way to move from fragmented inputs to a trusted daily point of view without spending hours manually reading, comparing and synthesizing.
Manual scanning across many sources, followed by ad hoc synthesis.
A structured flow that captures signals, evaluates evidence and produces a reviewed daily brief.
What I designed
A safer summary of the product work.
The public case study focuses on design decisions and workflow logic rather than production details. These are the parts that can be shown without exposing confidential project material.
Product framing
Defined the core job to be done: produce timely, evidence-backed event intelligence for a team working against a daily deadline.
Workflow design
Mapped the process from setup and watch planning through capture, synthesis, review and publication.
Information architecture
Organized the experience around workspace setup, signal capture, daily output, archive and review states.
Evidence model
Designed guardrails for confidence, attribution, weak claims and human approval before a brief is shared.
High-level architecture
The architecture can be shown as capability blocks, not screens.
To keep the project private, I represent the system at the level of inputs, processing stages, review gates and outputs. This shows the product thinking without exposing production UI, source strategy, data, prompts or implementation details.
Workspace and priorities
Defines the event context, audience, deadline, watch priorities and output expectations.
Capture and normalization
Turns public inputs and team observations into structured evidence that can be reviewed.
Synthesis and ranking
Clusters related signals, identifies themes and ranks takeaways by relevance and evidence strength.
Human approval
Flags weak claims, missing support and unclear attribution before the brief is shared.
Daily brief and archive
Publishes the daily view and preserves the record for later synthesis.
Long-form sessions become cited evidence.
The product also included a video intelligence capability. In the public case study, I show it as an architecture flow rather than a screen.
Impact and reflection
Less manual synthesis, more decision-ready context.
The clearest outcome was time saved: the workflow reduced the average effort required to go through signals, connect evidence and draw useful insights by 9 hours each week.
Average weekly time saved by replacing scattered research and manual synthesis with a structured capture, review and brief-generation workflow.
The team could move from open-ended signal review to a repeatable daily operating rhythm.
For AI-assisted strategy tools, the design challenge is not only output quality. It is trust, reviewability and clear human control.
My role, process, workflow diagrams, generalized product structure and approved impact metrics.
Production screens, real data, proprietary workflows, source strategy, prompts, internal architecture and client-specific outputs.