Overview
Aitomatic Inc. specializes in generative AI for industrial companies. In 2023, I owned the design of aiVA — a virtual advisor to streamline manufacturing operations and make efficient diagnoses by preserving domain knowledge.
Problem Statement
Field service engineers at manufacturing companies face many challenges: they have to install, troubleshoot issues, and fix machinery problems for customers under time pressure. They need a fast problem solving method than scanning bunches of documents and wasting time with trials and errors.
aiVA helps field engineers by providing access to the right knowledge with clear knowledge citations to any issue. aiVA also help detect issues by images and generate technical reports. It can increase first-time fix rates for the engineers.
Our envisioned UX should entail:
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Specialized for industrial engineers (count on the environment, mental models, time pressure)
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Tailored to specific problems and use cases
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Focused on problem-solving, not just knowledge retrieval
Design Process
1. Discover
I started with interviewing Sales on use cases raised when approaching prospects, target users, user problems, general and specific customer needs. I discussed with the Head of Product to map out the user benefits with the opportunities we could provide. As a small team, we had to be smart with our time and human resources.
2. Define
I identified the user persona, keeping my focus on the goal and expectation because the field engineers might not be tech-savvy, I could not force them into a thinking model that they were not familiar with.
3. Design
After aligning the user persona and expected UX flows, I created prototypes to communicate the final experience to the Product team, the Sales team and some field engineers in our customer organizations. Meanwhile, I also supported customer POCs to test the technical capabilities regarding the AI reasoning part and learn more about what the end-users might expect.
4. Deliver
From May 2023 to August 2023, I helped Sales sign several paid POCs with Petronas, Miura Boiler US, Tokyo Electron, EOS GmbH, and more. We launched aiVA MVP in September 2023.
Outcome
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Business Impact: Secured 06 POCs generating $500K in revenue and attracted an additional $500K in investments thanks to increasing customer interest.
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User Efficiency: Reduced time-to-repair by 30%, enhancing field engineer efficiency and customer satisfaction.
Conclusion
aiVA is another chance for me to switch my thinking to serve an unique user segment: field service engineers. The project showed me the importance of understanding user contexts and iterating rapidly to meet user evolving needs.