[Project] Designing an AI-Assisted SaaS Product: Theme Engine

Kat de la Fuente

UX Researcher
UX Designer
Product Designer
Axure
Sketch
Zeplin

What is Theme Engine?

Theme Engine is a qualitative research tool on Avalanche's platform that uses human-in-the-loop machine learning to enable researchers to listen to and analyze thousands of full, human responses—going beyond the limited insights found in solely quantitative research.

My role as a Senior Product Designer

Designs flows and screens for internal and external facing tools
Designs and build prototypes for usability testing and investor demos
Partners with Data Scientists to design with Interactive Machine Learning (IML) and NLP
Partners with Product Managers on product discovery studies
Supports software engineering team using Agile Workflow
Facilitates cross-functional meetings for open communication
Creates documentation to support product and engineering

Main Collaborators

Malaika Paquiot | Chief Product Officer Parul Ravel | Product Manager Raman Jhajj | Director of Engineering William Hakim | Software Engineer Miranda Pattyn | Software Engineer Paromita Sengupta | Software Engineer

The Goal

Enable researchers to understand people at scale

Conventional research methods mean you either get quantity or depth – not both.

If you surveyed 10,000 people with multiple choice questions, the results would be simple to quantify and analyze. To listen to and understand an audience's perspective in a more nuanced way, you may need to conduct interviews or focus groups.

What if you could listen to and understand an audience of 10,000 in their own words?

Capturing nuanced insights
Deepening understanding
Uncovering meaningful trends
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