Restaurant discovery and a Future Focused Social Media platform for Foodies
ReserveDine (Hereby referred as client) B2C focused application that provides restaurant discovery, table reservation, reviews, deals and experiences at restaurants as services to the Diners along with a social media platform for the foodies to interact.Download Case Study
The vision of ReserveDine was very high, the market that it wanted to capture already had lot of competition, but the business model that it wanted to bring was different and thus we started extending our technology support to reach the vision of our client. All they wanted was
According to the market research made, client kept forward their understanding about the current operation standards of the industry.
We extended our development services to
The customers of our clients can interact with the product through any of the above mentioned platforms.
According the usecases provided a user can generate the content in textual or media format in the form of reviews at a restaurant, checkins, menu level reviews and story posting. All this data either textual or media based (Images) have to captured seamlessly and to be used for further back - end analysis for the AI engine.
The Users are provided with leadership boards with the respect to the reviews that they are given and other people can follow each other to get the updates from that foodie. Each user can tag their fellow foodies on they posts creating a whole chain of interactions where the tagged foodies can start a conversation over the replies to the post.
Dine Buzz is a timeline for a city which includes posts from the foodies of the city and their reviews on the restaurant's or menu items or their checkins.
Using the cutting edge VR technology we could provide a way to capture the inside view of the restaurant in a 360 degree format of the image and are showcased on website and applications, to give the customer a better insight about the interiors of the restaurant.
ReserveDine is powered by a in house image compressor called RaviVerma which is essential since user generated images if are heavy gives a sluggish experience to the users. RaviVerma uses lossless compression techniques to reduce the size of the images by almost keeping the quality intact.
An AI engine is been built powered with machine learning models to provide better suggesstions to the users understanding their taste buds and preferences.
ReserveDine wants to come up with new crypto token of itself as a incentive to the foodies and restaurants. We have worked on content model consensus on the basis of proof of intelligence and proof of voting systems, and building smart contract over the ERC20 standard of Ethereum.