SaaS APp
Designing a GenAI-Powered App Suite for the SDLC
To design a comprehensive generative AI-powered suite that supports and enhances the entire Software Development Lifecycle (SDLC). The platform bridges gaps between ideation, requirements, development, testing, and release through contextual AI insights, collaborative workflows, and explainable AI outputs.
The goal was to deliver an intelligent, trustworthy, and scalable UX that empowers cross-functional teams while maintaining control, transparency, and enterprise-grade governance.
Timeline
15 weeks - Research, strategy, flows, wireframes, high-fidelity UI, and AI interaction design.
Background
Software teams today struggle with fragmented tools, manual work, and poor visibility across development stages.
Requirements gathering is laborious
Code quality and test coverage lacks automation
Release risk assessment is disconnected
Teams work in silos with limited cross-role collaboration
Existing AI tools mostly operate as isolated point solutions with limited trust and integration into real project data.
There was a clear need for an AI platform embedded directly into SDLC workflows that is explainable, auditable, and actionable.
The process for Black Vox includes research to understand user needs, wireframes to define structure, and high-fidelity designs for an intuitive interface. Prototypes are tested for usability, and developer-ready files ensure a smooth implementation.
Research & Planning
Conducted stakeholder interviews with product, engineering, QA, and leadership.
Mapped pain points, goals, and AI expectations for each persona.
Defined AI UX principles: explainability, control, context, and collaboration.
Information Architecture
Structured the suite into modular apps tied to SDLC stages.
Defined cross-app navigation to maintain context and reduce cognitive load.
Wireframes & Flows
Created task flows for core actions: prompt, review AI insight, accept/edit/reject.
Designed prompt surfaces, contextual AI panels, and confidence indicators.
High-Fidelity UI
Applied a scalable enterprise design system with AI-specific patterns.
Developed UI components for prompts, AI responses, traceable references, and feedback loops.
Validation & Iteration
Conducted usability testing with real SDLC teams.
Iterated on flows to improve clarity, trust cues, and transparency.
Enhances collaboration with real-time annotations, simplifies video uploads with drag-and-drop functionality and version control, streamlines workflow through customizable roles and permissions, accelerates review with AI-powered transcription and scene detection, and boosts productivity with a mobile-friendly interface for on-the-go feedback.
Real-Time Collaboration
Implemented frame-specific annotations and threaded comments to enable seamless real-time feedback.
Seamless File Upload & Management
Developed an easy drag-and-drop interface for video uploads with version control to manage project iterations.
Customizable User Roles & Permissions
Introduced granular user roles to control access and editing capabilities for different team members.
AI-Powered Transcription & Scene Detection
Integrated AI to automatically transcribe video content and detect key scenes for easy navigation.
The project successfully enhanced user engagement, streamlined workflows, and improved overall efficiency, resulting in a positive impact on user satisfaction and business outcomes.
Improved Collaboration Efficiency
40% reduction in project turnaround time due to real-time feedback and centralized communication.
Increased User Engagement
Higher adoption rates among creative teams due to intuitive design and seamless integrations.
Scalability
Platform ready to handle multiple teams and large projects simultaneously.
Positive Feedback
High satisfaction scores in post-launch surveys, with users praising ease of use and time-saving features.
Revenue Growth
Monetized via subscription plans with tiered pricing for individuals, small teams, and enterprises.