Since no direct competitors were solving this problem effectively, I expanded my research beyond traditional email tools. I analyzed platforms like Make.com, Zapier, ClickUp, Beehiv, and Height—all known for their automation capabilities.
The Three-Step Automation Flow – Every platform follows a similar pattern.
Trigger – Defines what starts the automation (e.g., receiving an email)
Conditions – Filters the data before taking action (e.g., checking for keywords like "order" or "receipt")
Action – Determines what happens next (e.g., moving emails to a folder or deleting them)
Clarity and Simplicity Matter – While these tools are powerful, some are overwhelming for non-technical users. A balance between flexibility and ease of use is crucial.
AI as an Assistant, Not a Replacement – AI-powered suggestions help, but users still want control over their automation settings.
Users value clear visual indicators and categorization for tracking automation processes effectively.
Bird eye view
To ensure a seamless and intuitive experience, I designed the information architecture to simplify automation setup while maintaining flexibility for advanced users. The structure is built to guide users through a logical flow, reducing cognitive load and decision fatigue.
To ensure users can manage their email automation efficiently, I opted for a table view. Here’s why:
Clear & Organized Data – Users can quickly scan automation details at a glance.
Scalability – Works seamlessly even if users create 10-20+ automations.
Easy Management – Enables sorting, filtering, and bulk actions for better control.
Compact Yet Informative – Displays key details like automation name, trigger, conditions, and actions without clutter.
By using this approach, users get a structured and scalable way to handle their email automation rules while maintaining clarity and ease of use.
After finalizing the Email Automation Listing screen, the next step was designing the Create Automation flow with flexibility for all users. Instead of a one-size-fits-all approach, I introduced three options: Build from Scratch for full control, Build Using AI for guided automation, and Choose from Templates for quick setup. This ensures a seamless experience for both technical and non-technical users. Now, let’s see what happens when a user selects "Build Using AI."
Once the user selects "Build Using AI," they are taken to the Automation Builder, where AI suggests smart automation setups. I chose a chat-based interface to make interactions intuitive and familiar, allowing users to engage with AI at any stage—whether for creating, modifying, troubleshooting, or publishing automation. With conversational UIs becoming the norm, this approach minimizes cognitive load and ensures a seamless experience for all users.
Now, let’s proceed with the "Select all receipts from Swiggy/Zomato to Food Expenses" automation.
After selecting the AI-suggested automation, users can further customize the rule to fit their needs. In this case, let's add "Zepto" and "Blinkit" to the existing rule, ensuring receipts from these services are also categorized under Food Expenses.
Users can also edit the rule seamlessly by simply typing in the AI chat. Whether adding new senders, modifying conditions, or changing actions, the conversational interface makes adjustments quick and intuitive—no need to navigate complex settings. This keeps the experience smooth and efficient for all users.
When the user clicks the Test button, a modal pops up displaying the test results in a table view for clarity. To keep things simple and avoid overwhelming the user, only five sample emails are shown. This helps users quickly verify if the rule is working as expected without unnecessary complexity.
In this project, I efficiently utilized the 48-hour timeframe by dedicating one full day to research and the other to designing the flow. The research phase allowed me to gain a deep understanding of automation and email sorting, while the design phase focused on creating an intuitive flow for creating and editing automation rules. Despite the limited time, I was able to learn a lot about automation processes and apply that knowledge to craft a well-structured design. This project helped me enhance both my technical understanding and design skills.
Why I'm the Right Fit for Nexera.ai 🚀
Hiring me would be one of your best investments for Nexera.ai. While I can’t predict the exact design results upfront, I’m confident that with feedback, the design can be refined and improved. I’m always open to learning, accepting my mistakes, and growing from them. 📈
Ownership and Responsibility 💼: I take full ownership of the product, not just the design. No matter what role I take on, I’m committed to delivering a product that resonates with users.
Versatility 🎩: Since this is a startup, I’m happy to wear multiple hats. From design to marketing, I’m not afraid to take on different roles, including exploring development if needed. At the end of the day, it’s all about growing the company.
Continuous Learning 📚: I’m eager to keep learning and developing my skills to contribute more effectively.
I genuinely believe I would be a great investment for the company. Thanks for the opportunity to be part of something I truly admire. I love the product and the vision behind it and would love to contribute, if not now, then in the future. Best of luck with the product's growth! 🌱