Dialogo Base
User Research, UX/UI
2024
Dialogo is a conversational AI interface that transforms scattered documentation and industrial data into intuitive, context-aware interactions, making complex knowledge accessible through natural dialogue. It provides tailored interfaces for different users: operators, who access documentation and retrieve information, and admins, who upload content, monitor interactions, and oversee system performance.
Problem
Organizations often struggle with making sense of large amounts of scattered, unstructured data—from technical manuals and logs to real-time process information. Operators and specialists are forced to navigate siloed dashboards, static reports, and multiple systems that rarely communicate with each other. This fragmentation slows decision-making, increases errors, and makes troubleshooting unnecessarily complex. Admins face additional challenges in keeping documentation up-to-date, tracking user interactions, and ensuring knowledge flows efficiently across the organization.
Solution
Dialogo was designed as a conversational AI interface that simplifies how people interact with information. By combining natural language understanding, RAG-based knowledge retrieval, and LLM-powered dialogue, it transforms documents and system data into guided, context-aware conversations. Operators receive a streamlined interface to query documentation, retrieve troubleshooting steps, process guidelines, and status updates, all presented with adaptive prompts and visual aids. Admins access a complementary interface to upload and organize documentation, monitor user interactions, and track system performance. The platform’s modular architecture ensures seamless integration with both document repositories and live data streams.
Results
The result is a platform that turns static documentation and scattered data into a unified, interactive experience tailored to each user role. Operators can find answers faster and with greater clarity, reducing search time, minimizing errors, and improving confidence in decision-making. Admins can maintain an up-to-date knowledge base, monitor interactions, and optimize workflows across the organization. By reframing knowledge as a dialogue rather than a static resource, Dialogo empowers teams to resolve issues 24% more quickly than usual methods and work more efficiently, while ensuring knowledge is actively managed and accessible.
Problem
Organizations often struggle with making sense of large amounts of scattered, unstructured data—from technical manuals and logs to real-time process information. Operators and specialists are forced to navigate siloed dashboards, static reports, and multiple systems that rarely communicate with each other. This fragmentation slows decision-making, increases errors, and makes troubleshooting unnecessarily complex. Admins face additional challenges in keeping documentation up-to-date, tracking user interactions, and ensuring knowledge flows efficiently across the organization.
Solution
Dialogo was designed as a conversational AI interface that simplifies how people interact with information. By combining natural language understanding, RAG-based knowledge retrieval, and LLM-powered dialogue, it transforms documents and system data into guided, context-aware conversations. Operators receive a streamlined interface to query documentation, retrieve troubleshooting steps, process guidelines, and status updates, all presented with adaptive prompts and visual aids. Admins access a complementary interface to upload and organize documentation, monitor user interactions, and track system performance. The platform’s modular architecture ensures seamless integration with both document repositories and live data streams.
Results
The result is a platform that turns static documentation and scattered data into a unified, interactive experience tailored to each user role. Operators can find answers faster and with greater clarity, reducing search time, minimizing errors, and improving confidence in decision-making. Admins can maintain an up-to-date knowledge base, monitor interactions, and optimize workflows across the organization. By reframing knowledge as a dialogue rather than a static resource, Dialogo empowers teams to resolve issues 24% more quickly than usual methods and work more efficiently, while ensuring knowledge is actively managed and accessible.
Reach Life
Service Design, UX/UI
2023
Problem
The journey out of debt is often broken across multiple tools and services that don’t communicate. Users may discover general advice on one platform, calculate repayment options on another, and attempt to track expenses in a standalone app. This fragmentation forces repetitive data entry, causes inconsistencies, and makes it difficult for people to connect long-term planning with everyday behavior. Combined with the emotional strain of debt and the complexity of financial concepts, this lack of continuity undermines user trust and engagement.
Solution
Reach Life delivers a coordinated service built around three interlinked touchpoints: the website, the Debt Calculator, and the Debt Guru app. The website is the entry point, setting the tone with accessible education and a clear invitation to begin a personalized plan. From there, users transition to the Debt Calculator, a desktop tool that translates their financial inputs into clear repayment strategies, using simple visuals to demystify complex choices. Once a plan is chosen, it flows directly into the Debt Guru mobile app, which supports the user day-to-day with automated expense tracking, reminders, and motivational nudges. By ensuring data continuity, consistent design language, and emotional coherence across all three touchpoints, Reach Life transforms a fragmented journey into an integrated service experience—guiding users seamlessly from awareness, to planning, to daily execution on the path toward financial stability.
The journey out of debt is often broken across multiple tools and services that don’t communicate. Users may discover general advice on one platform, calculate repayment options on another, and attempt to track expenses in a standalone app. This fragmentation forces repetitive data entry, causes inconsistencies, and makes it difficult for people to connect long-term planning with everyday behavior. Combined with the emotional strain of debt and the complexity of financial concepts, this lack of continuity undermines user trust and engagement.
Solution
Reach Life delivers a coordinated service built around three interlinked touchpoints: the website, the Debt Calculator, and the Debt Guru app. The website is the entry point, setting the tone with accessible education and a clear invitation to begin a personalized plan. From there, users transition to the Debt Calculator, a desktop tool that translates their financial inputs into clear repayment strategies, using simple visuals to demystify complex choices. Once a plan is chosen, it flows directly into the Debt Guru mobile app, which supports the user day-to-day with automated expense tracking, reminders, and motivational nudges. By ensuring data continuity, consistent design language, and emotional coherence across all three touchpoints, Reach Life transforms a fragmented journey into an integrated service experience—guiding users seamlessly from awareness, to planning, to daily execution on the path toward financial stability.
Kodelivery
User Research, UX/UI
2023
Kodelivery is an AI-powered SaaS platform designed to optimize logistics operations across various delivery types. It automates and simplifies delivery management, offering scalable solutions that integrate advanced technologies like real-time traffic data, IoT, and digital twin models to enhance fleet and warehouse efficiency.
Problem
The logistics market has experienced continuous growth, creating increasingly complex challenges for delivery operators. Key issues include managing multiple warehouses, optimizing truckload capacity, minimizing delivery costs, reducing drivers’ time on the road, and lowering the environmental impact of operations. Additionally, delivery planning must be adaptive to dynamic conditions such as real-time traffic and diverse vehicle types, which can be difficult to handle manually or with basic tools.
Solution
Kodelivery addresses these challenges with a flexible AI-driven optimization engine that automates route planning and delivery scheduling based on customizable constraints like vehicle profiles, delivery windows, and loading/unloading processes. The platform offers bulk address geolocation, queue optimization, real-time rescheduling, and integration with ERP and CRM systems via API. Developed through stakeholder interviews with fleet operators, small freight firms, and last-mile delivery services, Kodelivery incorporates practical insights for real-world usability. Its user-centric design ensures efficient fleet orchestration, reduction of empty trips, fuel savings, and lowered CO2 emissions, providing a robust tool for modern logistics management.
Problem
The logistics market has experienced continuous growth, creating increasingly complex challenges for delivery operators. Key issues include managing multiple warehouses, optimizing truckload capacity, minimizing delivery costs, reducing drivers’ time on the road, and lowering the environmental impact of operations. Additionally, delivery planning must be adaptive to dynamic conditions such as real-time traffic and diverse vehicle types, which can be difficult to handle manually or with basic tools.
Solution
Kodelivery addresses these challenges with a flexible AI-driven optimization engine that automates route planning and delivery scheduling based on customizable constraints like vehicle profiles, delivery windows, and loading/unloading processes. The platform offers bulk address geolocation, queue optimization, real-time rescheduling, and integration with ERP and CRM systems via API. Developed through stakeholder interviews with fleet operators, small freight firms, and last-mile delivery services, Kodelivery incorporates practical insights for real-world usability. Its user-centric design ensures efficient fleet orchestration, reduction of empty trips, fuel savings, and lowered CO2 emissions, providing a robust tool for modern logistics management.
Akroma OS Interface Study
Design System Ops, UX/UI
2024 – in progress
Context
The project is part of an open-source OS design system research proposal for Nothing products, aiming to create a cohesive and flexible ecosystem across mobile devices. It addresses the need for a modern interface that combines usability, personalization, and adaptability while aligning with the brand’s forward-thinking approach to technology.
Solution
Akroma is an open-source mobile OS interface designed to enhance usability and personalization. The project integrates human-centered design, visual prototyping, modular UI systems, and experimental interaction models to redefine how users engage with their devices. Current iterations feature unified communication flows, an adaptive alert system based on sensor data, and customizable notifications.
The design and research process is ongoing, with current testing and refinement ensuring that Akroma evolves into a flexible, community-driven interface that adapts to individual needs and grows with its users.
The project is part of an open-source OS design system research proposal for Nothing products, aiming to create a cohesive and flexible ecosystem across mobile devices. It addresses the need for a modern interface that combines usability, personalization, and adaptability while aligning with the brand’s forward-thinking approach to technology.
Solution
Akroma is an open-source mobile OS interface designed to enhance usability and personalization. The project integrates human-centered design, visual prototyping, modular UI systems, and experimental interaction models to redefine how users engage with their devices. Current iterations feature unified communication flows, an adaptive alert system based on sensor data, and customizable notifications.
The design and research process is ongoing, with current testing and refinement ensuring that Akroma evolves into a flexible, community-driven interface that adapts to individual needs and grows with its users.
Spectralize
User Research, UX/UI
2023
Spectralize is a collaborative SaaS platform that bridges spectroscopy and production through unified workflows.
Context
Workflows in spectroscopy and production were fragmented across multiple platforms, repositories, file formats, and locations, making collaboration between labs and production teams inefficient and error-prone. Chemometricians, analytical labs, and production operators each relied on separate tools that did not communicate seamlessly, resulting in duplicated effort, longer processing times, and increased potential for mistakes.
Solution
The team rationalized the wide array of tools, methodologies, and practices used at different stages of spectral analysis, calibration, and fit. By aligning the needs of both analytical experts and production operators, Spectralize was designed as a unified, collaborative SaaS platform with two dedicated access interfaces: Spectralize Data Lab, tailored for labs and chemometricians, and Spectralize Process, optimized for operators on the production line.
Results
The outcome is a comprehensive platform where diverse stakeholders collaborate seamlessly between spectroscopy labs and production environments. Spectralize integrates data sources, manages calibration models, monitors processes in real-time, and connects with ERP systems—all within user-friendly interfaces adapted to each role. By bridging the gap between research and production, the platform not only enhances accuracy and collaboration but also reduces mistakes by 20% and speeds up overall workflows by 32%, delivering measurable improvements in efficiency and reliability across spectroscopy-driven processes.
Context
Workflows in spectroscopy and production were fragmented across multiple platforms, repositories, file formats, and locations, making collaboration between labs and production teams inefficient and error-prone. Chemometricians, analytical labs, and production operators each relied on separate tools that did not communicate seamlessly, resulting in duplicated effort, longer processing times, and increased potential for mistakes.
Solution
The team rationalized the wide array of tools, methodologies, and practices used at different stages of spectral analysis, calibration, and fit. By aligning the needs of both analytical experts and production operators, Spectralize was designed as a unified, collaborative SaaS platform with two dedicated access interfaces: Spectralize Data Lab, tailored for labs and chemometricians, and Spectralize Process, optimized for operators on the production line.
Results
The outcome is a comprehensive platform where diverse stakeholders collaborate seamlessly between spectroscopy labs and production environments. Spectralize integrates data sources, manages calibration models, monitors processes in real-time, and connects with ERP systems—all within user-friendly interfaces adapted to each role. By bridging the gap between research and production, the platform not only enhances accuracy and collaboration but also reduces mistakes by 20% and speeds up overall workflows by 32%, delivering measurable improvements in efficiency and reliability across spectroscopy-driven processes.