EazyHelp

Services at your Fingertips!

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Inspiration

Even in these modern days, one has to search a lot to find a tradesman like electrician, plumber, etc. The common methods include asking for reference, searching online on various portals or using different mobile apps. However, a lot of people aren't comfortable with a new interface which comes with every app they install. Also, the people who provide these services lack a sophisticated platform to access all their appointments in an easy manner. Facebook's Messenger platform has a strong userbase of about 150 million people in India, and almost everyone of these knows how to chat with another person through messenger interface.

Hence, if the services required in daily life can be booked through Messenger in conversational manner, then it would be both easy and time saving for both the parties - and by bringing the exchange of information between the two sides online, we aim to contribute to a smart city.

What it does

  • For client: People who wish to avail the services of a tradesman first need to send a message about their requirements to the Messenger Chatbot. The chatbot will ask for client's location and will provide them a list of all the tradesmen who provide that service in their neighborhood. As soon as the user selects a tradesman, they are provided with the contact details of the tradesman.

Also, the user can select a time-slot and provide a short description of his problems/needs so that their needs can be catered in a more better way.

  • For tradesmen: People who wish to move offer their services through our portal need to register themselves as a helper. When a user chooses to fix an appointment with them, a notification message is sent to the tradesman. Also, we provide them with a portal to manage all their appointments at once.

How we built it

  • We used the Facebook Messenger Platform to build a chatbot called EazyHelp. The programming language used to create back-end is Python. Flask (a micro web framework in Python) was used to create a web server.

  • mongoDB was used as a database which was hosted on cloud using mLab. A python client for interacting with mongoDB, pyMongo was used.

  • Api.ai was used for extracting intents and entities from user queries.

Challenges we ran into

  • Implementing a seamless conversation flow in a chatbot is a pretty challenging task and one needs to consider all possible loop-holes in the conversation flow.

  • Our third team member who handles most of the frontend is down with fever, so we had to agree upon an idea that won't require too much frontend.

Accomplishments that we're proud of

  • We were unable to come up with anything concrete up until 12AM, but still were able to come up with a decent product with 1/3rd of our team not present here.

What we learned

  • We learned to manage work with which we aren't really proficient, and the importance of teamwork in such a tricky situation.
  • On a side note, I'll never eat too much of free food. I am having pain since yesterday.

What's next for EazyHelp

  • Currently it's free for a tradesman to register themselves with EazyHelp. We would like to implement a system for revenue generation from tradesmen.
  • A complete dashboard for tradesman to manage their appointments more effectively.
  • Implement a system of ratings for tradesmen to provide clients with better results.
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