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AI Tech Debt Platform
AI Tech Debt Platform
AI Tech Debt Platform
AI Tech Debt Platform
Made for
Made for
Made for
Cubyts Technologies
Cubyts Technologies
Cubyts Technologies
Cubyts Technologies
Year
Year
Year
2023-2025
2023-2025
2023-2025
2023-2025
End-to-end product experience for an AI-driven tech debt intelligence platform, from MVP to enterprise-ready launch.
End-to-end product experience for an AI-driven tech debt intelligence platform, from MVP to enterprise-ready launch.
End-to-end product experience for an AI-driven tech debt intelligence platform, from MVP to enterprise-ready launch.
Overview
Overview
Overview
Overview
Cubyts is an AI-Driven Tech Debt Resolution Platform built to help software teams identify, predict, and resolve technical debt in real time. As the sole designer at the startup, I was responsible for all design touchpoints, from product innovation and feature definition to developer handoffs, design system maintenance, and marketing collaterals. The platform addresses three critical pain points in software development: compliance gaps, feature drift, and rework which enabled teams to ship better software, faster.
Cubyts is an AI-Driven Tech Debt Resolution Platform built to help software teams identify, predict, and resolve technical debt in real time. As the sole designer at the startup, I was responsible for all design touchpoints, from product innovation and feature definition to developer handoffs, design system maintenance, and marketing collaterals. The platform addresses three critical pain points in software development: compliance gaps, feature drift, and rework which enabled teams to ship better software, faster.
Cubyts is an AI-Driven Tech Debt Resolution Platform built to help software teams identify, predict, and resolve technical debt in real time. As the sole designer at the startup, I was responsible for all design touchpoints, from product innovation and feature definition to developer handoffs, design system maintenance, and marketing collaterals. The platform addresses three critical pain points in software development: compliance gaps, feature drift, and rework which enabled teams to ship better software, faster.
Cubyts is an AI-Driven Tech Debt Resolution Platform built to help software teams identify, predict, and resolve technical debt in real time. As the sole designer at the startup, I was responsible for all design touchpoints, from product innovation and feature definition to developer handoffs, design system maintenance, and marketing collaterals. The platform addresses three critical pain points in software development: compliance gaps, feature drift, and rework which enabled teams to ship better software, faster.
Made for
Made for
Made for
Made for
Cubyts Technologies
Cubyts Technologies
Cubyts Technologies
Cubyts Technologies
Industry
Industry
Industry
Industry
B2B SAAS
B2B SAAS
B2B SAAS
B2B SAAS
Context
Context
Context
Context
System Design
System Design
System Design
System Design
MVP to Scale
MVP to Scale
MVP to Scale
MVP to Scale
Product Design
Product Design
Product Design
Product Design
Content
Content
Content
Content
Modular Development
Modular Development
Modular Development
Modular Development
Duration
Duration
Duration
Duration
1.5 years
1.5 years
1.5 years
1.5 years
The Challenge
The Challenge
The Challenge
The Challenge
Technical debt is an invisible but costly reality in software development. It accumulates through rushed deadlines, misaligned processes, and incomplete documentation which causes compliance gaps, feature drift, and endless rework. Teams had no intelligent, proactive way to surface or resolve these issues before they compounded. The design challenge was to make a deeply complex, data-heavy AI system feel navigable, actionable, and trustworthy for technical users.
Technical debt is an invisible but costly reality in software development. It accumulates through rushed deadlines, misaligned processes, and incomplete documentation which causes compliance gaps, feature drift, and endless rework. Teams had no intelligent, proactive way to surface or resolve these issues before they compounded. The design challenge was to make a deeply complex, data-heavy AI system feel navigable, actionable, and trustworthy for technical users.
Technical debt is an invisible but costly reality in software development. It accumulates through rushed deadlines, misaligned processes, and incomplete documentation which causes compliance gaps, feature drift, and endless rework. Teams had no intelligent, proactive way to surface or resolve these issues before they compounded. The design challenge was to make a deeply complex, data-heavy AI system feel navigable, actionable, and trustworthy for technical users.
Technical debt is an invisible but costly reality in software development. It accumulates through rushed deadlines, misaligned processes, and incomplete documentation which causes compliance gaps, feature drift, and endless rework. Teams had no intelligent, proactive way to surface or resolve these issues before they compounded. The design challenge was to make a deeply complex, data-heavy AI system feel navigable, actionable, and trustworthy for technical users.
The Solution
The Solution
The Solution
The Solution
As the product grew from MVP to enterprise scale, so did the scope of my design work. I started by rapidly prototyping a focused MVP, then evolved the platform through continuous pilot feedback, GenAI integration, and enterprise deployment needs. Along the way, I built and maintained the design system, drove feature definition with stakeholders, and supported sales through marketing collaterals. My most detailed contribution was designing "Repository", a feature that brings structure to the chaos of scattered documentation across large codebases, using AI to surface context exactly when developers need it.
As the product grew from MVP to enterprise scale, so did the scope of my design work. I started by rapidly prototyping a focused MVP, then evolved the platform through continuous pilot feedback, GenAI integration, and enterprise deployment needs. Along the way, I built and maintained the design system, drove feature definition with stakeholders, and supported sales through marketing collaterals. My most detailed contribution was designing "Repository", a feature that brings structure to the chaos of scattered documentation across large codebases, using AI to surface context exactly when developers need it.
As the product grew from MVP to enterprise scale, so did the scope of my design work. I started by rapidly prototyping a focused MVP, then evolved the platform through continuous pilot feedback, GenAI integration, and enterprise deployment needs. Along the way, I built and maintained the design system, drove feature definition with stakeholders, and supported sales through marketing collaterals. My most detailed contribution was designing "Repository", a feature that brings structure to the chaos of scattered documentation across large codebases, using AI to surface context exactly when developers need it.
As the product grew from MVP to enterprise scale, so did the scope of my design work. I started by rapidly prototyping a focused MVP, then evolved the platform through continuous pilot feedback, GenAI integration, and enterprise deployment needs. Along the way, I built and maintained the design system, drove feature definition with stakeholders, and supported sales through marketing collaterals. My most detailed contribution was designing "Repository", a feature that brings structure to the chaos of scattered documentation across large codebases, using AI to surface context exactly when developers need it.
The Result
The Result
The Result
The Result
The platform evolved from an MVP with two pilot customers to securing partnerships with Google Cloud and the NVIDIA Inception Program, landing the first paying customer, and scaling to six active implementations all within a single year. The design system and iterative design process directly supported the speed of development and enterprise readiness of the product.
The platform evolved from an MVP with two pilot customers to securing partnerships with Google Cloud and the NVIDIA Inception Program, landing the first paying customer, and scaling to six active implementations all within a single year. The design system and iterative design process directly supported the speed of development and enterprise readiness of the product.
The platform evolved from an MVP with two pilot customers to securing partnerships with Google Cloud and the NVIDIA Inception Program, landing the first paying customer, and scaling to six active implementations all within a single year. The design system and iterative design process directly supported the speed of development and enterprise readiness of the product.
The platform evolved from an MVP with two pilot customers to securing partnerships with Google Cloud and the NVIDIA Inception Program, landing the first paying customer, and scaling to six active implementations all within a single year. The design system and iterative design process directly supported the speed of development and enterprise readiness of the product.
PORTFOLIO
PORTFOLIO
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CHECK OUT SOME MORE
CHECK OUT SOME MORE
CHECK OUT SOME MORE
Bayer x Parsons
Bayer x Parsons
Bayer x Parsons
Strategic Design
System Design
UX research
Cross-Functional Collaboration
Buttercookies
Buttercookies
Buttercookies
Design System
Design Tokens
Atomic Design
Dev Handoff
Build with me
Build with me
Build with me
Build with me
Open to internships, full-time roles, and meaningful collaborations
Open to internships, full-time roles, and meaningful collaborations
Open to internships, full-time roles, and meaningful collaborations
.