Generative AI
AI - It’s everywhere you look these days.
Enterprise is rushing to adopt AI to solve complex problems and save money. The problem is doing it successfully and unobtrusively.
Why successfully? When you ask multiple questions from data lakes with large amounts of end points and options, it can get complicated quickly.
Meeting customers where they are is one thing we heard over and over again. While our first concepts were focused heavily on the chat experience that had become ubiquitous with ChatGPT and Gemini, many of our customers just want to find things faster, not necessarily get generative answers.
Chat experience and optional paths for further investigation
Getting users to an area where they can further explore became one of our key objectives. Helping them create complex data visualizations and getting them to to the data quickly so they can define the best course for remediation is a huge time savings for the.
Research
“We’re not asking AI to remediate by any means. We’re asking, can you assist me with all of this data? Where should I be focusing?”
The research really validated some our out design concepts. Data integrity and finding it quickly is of utmost importance. After they understand and trust the data, they are more willing to solve for the issues they can detect.
Here’s a great example of that where it was included in the data explorer and used to create a usable chart.
Want to learn more about my experience helping us define our direction of complex enterprise UX solutions? Send me a message! Thanks for looking.