FIVA
Completed
AI Solutions
Client Acquisition
Ethnographical studies
Contextual observations
Team
Contribution
Tools
Timeline
Context
FIVA was developed to address inefficiencies in fault diagnosis within a leading aviation company. Engineers struggled with disconnected tools, ambiguous fault codes, and over-reliance on senior staff. I led UX research and design efforts to streamline these processes through AI-guided workflows and improved system integration.
Backstory: Aviation engineers at Sabiha Gökçen Airport experienced delays in fault isolation due to fragmented data systems and manual processes.
The Problem: Junior engineers lacked autonomy, relying on senior staff for complex fault resolutions.
What I Did: Conducted site visits, shadowed engineers (contextual observations), and designed AI-integrated workflows to empower junior staff.
Why: To reduce fault resolution times and create scalable decision-making tools that improve efficiency across the team.
Impact: Demonstrated a 30% faster fault completion rate compared to the historical manual workflow. Validating the prototype’s ROI potential through stakeholder presentations.
Key Takeaways
Adapting to Complex Domains: This project honed my ability to quickly learn and adapt to highly technical environments, such as aerospace engineering.
Managing Cross-Functional Teams: I gained experience in working across product, engineering, and design teams, balancing multiple stakeholder priorities in a high-pressure project setting.
Building Resilience in Uncertainty: The abrupt end of the project highlighted the importance of being adaptable and continuing to find value in work, even when circumstances change unexpectedly.
😋 Turkey is a beautiful country with an even more beautiful culture and cuisine. I ended this part of my career journey on a high note.












