Taxi Booking and Dispatch Software - Taxi in New York - Digiteum
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Taxi Dispatch Service in NY

Thanks to the plenty of taxi services such as Uber, Lyft and traditional Yellow Cab, it’s easy to get a ride in New York. Every taxi company has its differences. However, both old-timers and on-demand taxi apps offer more or less the same pricing concept — a passenger pays a certain price depending on the mileage.

Ploiny is a novel service in the market that offers disruptional pricing model and enhanced customer experience thanks to innovative taxi booking and dispatch system. Like Ebay, it enables various drivers to offer prices for a requested ride and allows passengers to choose the best offer from different drivers. Moreover, dispatch system supports multilingual ordering — customers can call for a ride in English and Yiddish. Therefore, the Jewish people looking for a ride in New York City no longer need to switch to English for ordering a car.

cabs in new york
Ploiny taxi booking and dispatch service in New York
new york cab
Disruptional pricing model and enhanced customer experience thanks to innovative taxi booking and dispatch system.

Taxi Booking by Voice or Chat

Apart from bidding, the concept of Ploiny is not new. Passengers dial a certain number or type SMS with trip details, dispatcher connects to available drivers, drivers offer their prices, and once passengers choose the price, they get a ride. However, the technology behind this taxi dispatch software deserves attention for making this customer-centric experience smooth.

Voice interface

Today, Ploiny integrated with Twilio enables voice ordering in English and Yiddish. Once passenger dials to get a car, a dispatcher registers all necessary details on the system’s web panel and creates a ride. The rest is fully automated thanks to the inbuilt voice answering system. Dispatch software calls for proposals from available drivers, manages the bids, accepts the choice passengers make using dial pads on their phones, informs the drivers and confirms the booking. Moreover, it can establish a direct connection — phone call or SMS — between a driver and a passenger, if needed.

NLP chatbot via SMS

Apart from traditional voice ordering, Ploiny allows to get a taxi in NY using SMS. For this purpose, a smart SMS chatbot works as a taxi dispatcher. The bot is built with Microsoft Bot Framework and trained to understand natural language. Thanks to Microsoft LUIS NLP engine, the chatbot understands user requests sent via SMS, asks for and collects necessary details of the trip, creates the ride and sends data for further processing into the system using API. Moreover, LUIS allows to train NLP chatbot relying on previous cab orders and improve its language understanding and response capabilities.

In the future, Ploiny taxi booking and dispatch service will improve. It’s planned to increase the number of channels for taxi ordering via chat and expand the chatbot to popular messengers, like Facebook Messenger and Telegram, substitute human operator with speech understanding technology to fully automate voice ordering, and build additional apps and web interfaces for passengers and drivers to enhance control options from any device or channel.

taxi in new york
Use voice interface and NLP chatbot in SMS for ordering a taxi in NY.
cabs in new york
Taxi dispatch software for semi-automated bid-based taxi booking by voice calls or SMS.

Highlights

  • Taxi dispatch software for semi-automated bid-based taxi booking by voice calls or SMS;
  • Integration with Twilio to enable telephony connection between passengers, operators and drivers;
  • Inbuilt voice answering system for automated voice ordering that supports both English and Yiddish;
  • NLP chatbot based on Microsoft LUIS engine trained to enable automated taxi ordering via SMS, collect passenger data and send it to Microsoft Azure storage;
  • Web panel for operators to register details, confirm rides, monitor rides status and history and for admins to create and store drivers’ profiles and operator roles.

PROJECT DETAILS

DATE: 2018

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