Enterprise Contract & Sales Analytics
Democratizing data access through modular architecture and conversational AI.
The Critical Challenge
Business managers were wasting too much time waiting for engineering teams to pull data reports for them. We needed to design a self-serve dashboard that anyone could use. By adding an AI-powered search, we made it possible for non-technical users to ask questions in plain English and instantly generate the exact charts and data they need to make fast decisions.
Who Are We Solving For?
Contract Managers
They need to track contract migrations and manage vendor agreements. This dashboard gives them a quick way to see high-level contract values without needing to ask for help or write database queries.
Sales Managers
They need to monitor regional sales and track product performance. This tool allows them to easily filter through complex sales data in real-time so they can adjust their strategies on the fly.
Dashboard Architecture & Customization
Adaptive Workspaces
Designed a highly flexible grid system where users can personalize their workspaces. Through an intuitive "Edit Dashboard" modal, users can select structural layouts, toggle specific graph widgets, and pin critical top-level KPIs (e.g., Average Handling Time, Total Resolved Issues).
Conversational AI
Natural Language to Data
Engineered a generative AI feature allowing users to input natural language requests, such as "display total number of contract worth over $100k". The system instantly outputs synthesized text summaries alongside auto-generated visual charts which can be saved directly to the dashboard.
Schema Visualizer
Visual Database Mapping
Translated complex backend architecture into a user-friendly visual schema builder. Users can visually trace relationships (Primary Keys, Foreign Keys) between distinct tables like Customers and Products without writing a single line of SQL.
Project Outcomes & UX Impact
Reduced Cognitive Load
Standardized the UI component library and utilized a cohesive, accessible color palette to make dense relational databases easily scannable.
Workflow Efficiency
Eliminated the need for SQL knowledge by introducing generative AI querying, allowing users to extract high-value insights instantly.
Increased Autonomy
Designed a highly modular architecture that empowers managers to customize layouts and pin critical KPIs without developer support.
