Case study
Job Signal
AI job-search intelligence platform
Turns a job seeker’s own application history into evidence about what is working, what is not, and what to test next.
- Status
- MVP / Active testing
- Role
Product concept and strategy
UX direction
AI workflow design
MVP development
01 — The problem
Trackers record activity. They don’t explain it.
Most job-search trackers record applications, interviews and outcomes. They do not answer the more useful questions:
- Which roles are actually producing interviews?
- Which CV version performs better?
- What requirements keep appearing?
- Where am I getting rejected?
- What should I change next?
02 — The product
An intelligence layer over the search.
Instead of simply tracking applications, Job Signal analyses the evidence accumulated during the search and turns it into patterns, insights and specific next experiments.
- 01
Application data
- 02
CV versions
- 03
Observed outcomes
- 04
Recurring patterns
- 05
AI interpretation
- 06
Strategy and next action
03 — How it works
How Job Signal turns application data into strategy.
Record the application
The user adds a job description and records an application. AI extracts structured information — requirements, seniority and work mode — which the user confirms before saving.
Keep CV versions separate
The user maintains different CV versions and associates them with different types of roles, so outcomes can be attributed to a specific version rather than the search as a whole.
Surface the patterns
Job Signal calculates measurable patterns across the accumulated application data, including funnel counts, interview rates by role family, CV performance and recurring employer requirements. These observed patterns remain separate from AI interpretation.
Turn evidence into strategy
AI interprets the accumulated evidence and generates a strategy report: what appears to be working, what is underperforming, how strong the evidence is, and one specific next experiment to test.
04 — What makes it different
From “what did I apply for?” to “what is this telling me?”
Traditional trackers answer
What did I apply for?
Job Signal is designed to answer
What is my application history telling me?
The product combines tracking, CV comparison, pattern detection and AI interpretation, so past applications can influence the next decision.
05 — The role of AI
AI does interpretation, not conversation.
Job Signal is not a chatbot. AI sits at defined points in the workflow, and its output is always tied back to the user’s own evidence.
- Extracts structured information from job descriptions
- Interprets patterns found across application data
- Connects CV versions, target roles and outcomes
- Identifies recurring employer requirements
- Generates evidence-linked strategy reports
- Suggests a specific next experiment rather than generic career advice
06 — Build status
MVP built and currently in active testing.
07 — Credit
Designed and built by Roselyne June
- Product concept and strategy
- UX direction
- AI workflow design
- MVP development