NSW State library visitor trying the finished Wriveted's Chat bot.

My Role

I supported the Wriveted team through multiple iterations of their product, as a UX designer. Together we rapidly prototyped the chat bot experience using LandBot and custom thermal printer integration. I also helped conduct design works with school children to build the ultimate chat bot.

Wriveted finds books that match a child’s interests, increasing their desire to read and improving literacy. Wriveted's chat bots are in NSW schools and also in the State Library of NSW Children’s Library. The team has worked closely with librarians to create an engaging experience for children to find books that match their interests and general reading ability.

The 1st prototype, was perfect for gathering feedback and engaging potential stakeholders.

Low Code Approach

The Wriveted team smartly iterated through lots of ideas cheaply to find product fit – this project was no exception. We stitched together some No-Code tools (Landbot.io, Airtable) with some JavaScript to build a low code prototype that we could rapidly iterate within a tight deadline.

We used a service called landbot.io to develop the chat bot experience. I helped push LandBot to the limit, using API calls, and custom logic to help achieve the experience set by the Wriveted team. Landbot's SDK allowed me to embed the chatbot in a web app, that could communicate with a Thermal printer on the same network. The Wriveted team used lego to fashion an physical unit for all the components.

The Wriveted team were able to use the prototype to collect feedback and attract keen stakeholders, which encouraged them to iterate the design into a model ready for production. I then helped rework the system to run on a Windows 10, Intel Compute stick. This system proved to be quite stable, and was installed into the NSW State Library to be used an enjoyed by young readers.

School students at our design workshop prototyping and providing input for the 2nd iteration.

A simple chat interface that enables unique recommendations based on the readers attributes.