Monte Carlo - AI Troubleshooting Agent Experience
Role
Product design and research
Company
Monte Carlo
Timeline
Jan 2023 - present
Problem
Monte Carlo provides data observability through a combination of out of the box and custom rules on various different data quality dimensions such as accuracy, validity, timeliness, consistency. We wanted to improve our troubleshooting and investigation offerings and improve time to resolution for incidents.
Solution
In this project we redesigned the UX and information architecture for the incident resolution experience to seamlessly integrate a new AI troubleshooting agent.
Case study and design walkthrough
Existing users in Monte Carlo have to traverse several investigation paths manually to identify the root cause of their data incident and get to resolution. Our goal was to build an AI troubleshooting agent that pursues all of these investigation paths and helps user validate or invalidate a hypothesis within a matter of minutes.
Existing incident investigation
Investigation with troubleshooting AI agent
