Jungle AI canopy

Lead Product Designer 2019-2020.

Enhancing Renewable Asset Management with Jungle AI’s Canopy

Jungle AI is a pioneering artificial intelligence company dedicated to optimizing the performance of renewable energy assets. At the heart of its offering is Canopy, a sophisticated AI-driven platform designed to provide in-depth analysis and monitoring of renewable assets. My role as a designer was pivotal in ensuring that Canopy is not only functional but also user-friendly and intuitive, allowing users to delve deeper into the components and subcomponents of their assets, pinpointing those that require attention.

2019 was a pivotal year for us at Jungle AI. We had to take a hard look at our processes and outcomes because, despite our best efforts, there were many misalignments and unclear problems when building the product. The outcome was not as successful as we had hoped. While the company had enjoyed success over the previous three years, the positive results often felt serendipitous rather than the result of meticulous planning. This realization was a catalyst for change, driving us to refine our approach and align our efforts more strategically.

Our clientele spans two distinct sectors: wind energy and heavy industry. Wind farm owners are typically eager and open-minded, always on the lookout for innovative tools that can streamline their operations and boost their profits. They welcome new technologies and are willing to experiment, providing us with a fertile ground for testing and refining our solutions. On the other hand, heavy industry players are more complacent, having settled for their existing tools because they get the job done. Their cautious nature means they require a more convincing argument to adopt new technologies.

Understanding these dynamics was crucial in shaping our approach. For the wind industry, our strategy involved rapid iteration and feedback loops, leveraging their openness to refine our offerings quickly. We focused on demonstrating clear, immediate benefits to build trust and demonstrate value. Conversely, for heavy industry, we knew we needed a more measured approach. This meant extensive testing, rigorous proof of concept phases, and a clear demonstration of long-term value to overcome their initial hesitance.

By addressing the unique needs and attitudes of these sectors, we aimed to create a more robust, user-centric product. This dual approach allowed us to cater to the enthusiastic experimentation of wind farm owners while providing the reliability and assurance demanded by heavy industry. The lessons learned from this period of reflection and recalibration have been instrumental in shaping our current success, enabling us to better serve our diverse customer base with precision and purpose.

Constrains

As the designer, I faced constraints typical in our field. Previous design attempts with two agencies had failed. The founders and head of product had strong, often conflicting assumptions, making decisions challenging. With a looming deadline, many features relied on assumptions rather than user research, driven by investor pressure. Grafana was our tool for presenting results.

House keeping

I introduced design workshops to the team as a safe space for everyone to express their ideas and thoughts. The main goals were to enhance cross-team collaboration, increase receptivity to feedback, and promote research-based solutions. We emphasized that we were tackling problems together, not competing against each other. We discouraged siloed work and ego-driven decisions, favoring fact-based solutions instead.

The solution path

We agreed to conduct qualitative research to better understand the problem space, apply previous learnings before my tenure, and commit to building from there. This approach ensured we leveraged past insights and grounded our solutions in real user needs, setting a strong foundation for our design process.

User Experience (UX) Design

• Seamless Navigation: Ensured that navigation within the platform is seamless, allowing users to move from high-level overviews to detailed component analyses effortlessly.
• Interactive Elements: Incorporated interactive elements such as clickable components and detailed sensor data pop-ups, enhancing user engagement and understanding.
• Customization Options: Provided customization options for users to tailor the platform to their specific needs, such as setting thresholds for warnings and choosing preferred data visualization formats.

User Interface (UI) Design

• Intuitive Dashboard: Developed a clean, intuitive dashboard that allows users to monitor asset performance at a glance.
• Component Visualization: Designed visual representations of asset components, enabling users to easily identify and drill down into specific areas requiring attention.
• Anomaly Indicators: Created clear and distinguishable anomaly indicators, helping users quickly spot and understand issues.

Usability Testing

• User Feedback Integration: Conducted usability testing sessions with potential users to gather feedback and refine the platform accordingly.
• Iterative Design Improvements: Made iterative improvements based on user feedback, ensuring that Canopy meets the practical needs of asset managers in the renewable energy sector.

Impact

The design enhancements significantly improved the user experience and functionality of Canopy, leading to:

• Increased Efficiency: Users can now quickly identify and address issues at the component level, reducing downtime and maintenance costs.
• Enhanced Decision-Making: Detailed insights into sensor anomalies and component performance enable better decision-making and proactive maintenance.
• Greater User Adoption: The intuitive and user-friendly design has led to higher adoption rates among asset managers, maximizing the impact of Jungle AI’s innovative technology.