UI Designer
Lofi wireframes, hifi mocks, prototyping
May 2024 - ongoing
Figma
Vama is a mobile chat app that currently offers basic messaging features. Along with developing core functionalities like the Meetings feature, our stakeholders plan to add AI capabilities soon. This case study outlines our concepts for Vama AI, including the features and designs we've explored. Note that this is still a work in progress!
AI plays a crucial role in today's tech world. To enhance the user experience in Vama, we aimed to offer personalised experiences and increase efficiency with automation. We identified two common user problems and developed AI-based solutions. Here’s a look at the two features and my proposed lo-fi solutions.
A high volume of unread messages makes it difficult to keep up with important conversations.
We can condense and highlight key points from unread messages, allowing users to quickly grasp the essence of conversations without having to read through every message in detail.
Cluttered and lengthy chat threads make it difficult to keep track of important conversations and tasks.
Implementing "Suggested Actions" can provide users with actionable tasks such as categorising messages, setting reminders, and integrating calendar events. This will help users efficiently organise their chats and maintain a tidy conversation flow.
After several rounds of ideation, our stakeholders approved the wireframes, allowing us to progress to high-fidelity mockups. Below are some of my designs for the two AI features mentioned earlier. Please note that these designs are still in development and have not yet been finalised.
After some discussion, we decided on two ways to access Vama AI:
When the user clicks on the Summariser feature, a pop-up slides up from the bottom displaying a preview of all unread chats. This preview includes the group/profile avatar and name, the number of unread messages, and a snippet of the last message sent in each chat.
When the user clicks on any of these cards, the AI begins generating a summary of that chat. Once the summary is ready, the user can choose to mark the chat as read or go directly into the chat.
I added new prompts to appear after the Conversation Summary is generated. These include features like "Chat Highlights" and "Key Contributors."
Users can also continue chatting with Vama AI and ask questions if they wish.
At the top of the Vama AI chat screen, users can slide along the carousel to select the "Vama AI Action Planner."
Once selected, a pop-up displays recommended actions, including calendar suggestions, group organisation, setting reminders, and more.
When users choose an action, tasks are automated with pre-filled text, dates, times, and contacts. For calendar suggestions, I designed it to open Google Calendar as we don't have a Vama Calendar yet.
We are still in the early stages of designing Vama AI, with much more to come. Currently, I am working on refining the two features above, as well as a deep search feature. Stay tuned for future updates!
