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Insi: AI-Powered Research Assistant

Insi is a conceptual B2B SaaS platform designed to solve the critical bottleneck of qualitative research synthesis for modern product teams. Leveraging AI, the tool transforms unstructured data from interviews, surveys, and feedback into clear, actionable themes and insights. As the sole product designer, I led the end-to-end design process from initial strategy and persona development to a high-fidelity, interactive prototype.

Click here to check the final interactive prototype.

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My Role

Product Designer (Product Design, Branding, Ideation, User Experience)

Tools

Figma, Notion, AI (for heuristic evaluation)

Timeline

4 Weeks (Conceptual Sprint)

1. The Problem & The Goal

The Problem

Product managers and UX researchers are drowning in qualitative data. They spend dozens of hours manually sifting through interview transcripts, user feedback, and survey responses. This manual process is not only slow and inefficient but is also prone to human bias, creating a major bottleneck that delays critical product decisions and leads to features built on stale insights.

The Goal

The primary goal for Insi is to reduce the average time-to-insight from weeks of manual work to a single afternoon of validation. By automating the most tedious parts of research synthesis, the platform aims to empower product teams to make faster, more confident, and truly user-centered decisions.

Target Users

Preeti, the Product Manager

Goal: Quickly validate or invalidate a hypothesis.
Frustration: Data is scattered, and synthesis is too slow for her agile team.

David, the UX Researcher

Goal: Find deep, unbiased themes for long-term strategy.
Frustration: Spends more time on manual "ops" work than on strategic analysis.

2. My Approach

I followed a condensed, end-to-end product design process to move from a high-level problem to a validated, high-fidelity solution.