LCP

AI based platform that augments restaurant frontlines

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Overview

Revolutionary AI-powered platform designed to enhance restaurant operations by seamlessly automating order-taking at drive-thrus, kiosks, and over the phone.

At A Glance

industry
Industry
Hospitality
region
Region
USA
duration
Duration
12 Weeks

Technical Stack

python
gcp
square
redis
fastapi
mqtt

Client Profile

The client is a SaaS provider in the USA, specializing in designing and building augmented assistants.

Challenge

  1. The client wanted to provide a faster order service to their customers, as their current order delivery was quite slow and their customers had to wait in the queue.
  2. The client wanted to automate certain tasks for current employees. This would allow them to focus on preparing the customer order and delivering it in a quick serviced fashion.
  3. The client wanted to promote cross-selling and upselling of products by suggesting great combo offers and great deals to the customer so that they would buy multiple items.
  4. The client also wanted to reduce the labor cost due to the shortage in the labor market and trends towards higher wages.
Image illustrating the AI-based platform optimizing restaurant frontlines - showcasing streamlined processes, automation, and data-driven insights

Solution

  1. Seaflux created artificial intelligence based multi-experience voice assistant system that handles and coordinates the customer experience, specifically for restaurants and retails, from answering questions to processing orders to finally upselling at the end of every transaction. 
  2. Voice assistant also interacts with customers via conversational AI functions at POS that replicate human interaction through listening to speech and responding using NLP.
  3. For better customer experience and a faster drive-thru process, the AI provides personalized recommendations based on their needs, preference, and customized order history.
  4. The AI model is based on NLP in a local server for customer interaction and processing orders. The recommendation system for cross-selling and upselling is created by training the ML model using the Decision Tree and Random Forest Algorithm.
  5. The AI solution is designed in a way such that the system works seamlessly with any modern cloud POS systems like Square, Brink, Toast, NCR, Omnivore, and many more.

Key Benefits

  1. A sharp increase in customers through the drive-thru line is handled using the AI assistant.
  2. 34% quarterly increase in drive-thru revenue by faster throughput of the customers.
  3. The AI solution offers a 10:1 ROI when compared to the cost to recruit, hire, train, and retain a “B” player, reducing the labor cost
  4. 28.7% increase in cross-selling & upselling of products, “frequently bought together” combos saw a substantial rise.

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