Case Study - Inteliome : Data Query Platform

Overview

In late 2022, I joined the Inteliome team to design a tool that lets users upload a PDF and chat with it. The idea was simple: make data more accessible through conversation. This was before tools like ChatGPT became mainstream.

Working closely with a dedicated AI research team, we built the initial version. As the product gained traction, our team expanded to 20 members. The platform's capabilities grew, integrating external data sources like Snowflake and Salesforce, supporting various data analysis files, and introducing features like data agents and multi-chat functionalities.

What I did

Design Journey

The AI landscape was evolving fast, with new competitors emerging weekly and pushing boundaries. We felt immense pressure to stand out and innovate. Our process had to be incredibly adaptive.

Market Watch: We constantly looked at similar AI products. What were they doing well? Where were they lacking? This ongoing competitor analysis helped us identify opportunities and stay relevant.

Quick Ideas: For new features, we didn't start with complex designs. We used lots of quick sketches and collaborative tools like Miro to brainstorm ideas rapidly with the team.

Concept First: Once a core concept felt right and was approved, then I would dive into the detailed UI/UX design and prototyping.

Hands-on Frontend: My involvement didn't stop at handing off designs. I actively worked with the frontend developers, often jumping into the code myself to fix minor UI issues, adjust spacing, ensure visual consistency, and polish the user experience after the basic feature structure was in place. This close loop ensured the final product matched the design intent closely.

Design System

In the midst of rapid feature development and team scaling, our key strategic decision was dedicating significant effort to building and refining the design system, including implementing design tokens.

It required upfront investment when pressure was high to just build features. We bet that this foundation would pay off massively in the long run by enabling faster development, ensuring consistency, simplifying maintenance, and making it easier to onboard new team members.

Mobile App Design & Development

Instead of shrinking the desktop product, we focused on what actually matters on mobile. We started not with layouts, but with feature prioritization—what users needed on the go, and what could be left out. This allowed us to simplify without sacrificing usefulness.

Inspired by popular tools our clients already used—like Microsoft Teams and Slack—we designed a mobile app that felt familiar and instinctive. We wanted users to feel at home, not confused.

Conclusion

The Inteliome platform has evolved significantly since its inception. It's now a comprehensive tool that helps users analyze and understand complex data through natural language conversations.

Personally, the most rewarding aspect of this project was the deep dive into creating and implementing the design system. Exploring different strategies, introducing tokens, and seeing how it streamlined the workflow between design and development was incredibly satisfying. Collaborating with such passionate individuals in the AI space was a constant source of learning and inspiration. It was a unique opportunity to contribute to the foundation of an innovative product during a pivotal moment in AI development.