FourKites AI Product
Design Direction
AI/ML
SaaS
Design Systems
Data Visualzation
Industry
Supply Chain
Project Type
AI Product Design
Client/Brand
FourKites
Overview
FourKites set out to build an enterprise-grade conversational AI assistant and risk assessment tool to make complex logistics and supply-chain data accessible through natural language. As Design Manager for the initiative, I helped shape the creative direction and experience vision for Kitebot (Later FinAI) the company’s first step toward an AI-powered future. The product was introduced as a Phase 1 Enterprise AI solution, designed to give users instant access to critical insights- shipment performance, appointment risks, emissions data- all through a simple conversational interface, prompts and touch-points within the existing FourKites platform.
Challenge
FourKites manages massive volumes of real-time logistics data across global carriers, warehouses, and customers. Users needed a faster, simpler way to surface insights without navigating dozens of dashboards or filters. The challenge was to define a clear, approachable experience that could interpret natural-language questions and return structured, reliable results — all while preserving brand trust and enterprise-grade simplicity. The solution also needed to proactively surface risks and recommend actions to help users prevent shipment delays and disruptions.
Partnered with product, engineering, and data science to establish how AI would live within FourKites, guiding design direction, shaping the interaction model,… Partnered with product, engineering, and data science to establish how AI would live within FourKites, guiding design direction, shaping the interaction model, and setting visual standards that influenced later AI experiences across the platform. The focus was balancing enterprise data visualization with consumer-grade simplicity, with a framework covering tone, intent recognition flows, and contextual prompts that made AI feel like a natural extension of the product, not a bolt-on feature.
Impact
Increased user retention by 50% and reduced workflow friction by 60%, validating conversational and proactive AI as a viable enterprise UX model.
