How Vanus AI Improved Sales for an Online Food Vendor
Table of content
Challenge
In the bustling food market of Benin City, Nigeria, Jegede Jollof encountered a pressing issue. Despite their growing popularity, the influx of orders surpassed their capacity, leading to significant delays in fulfilling customer requests. This resulted in frustrated patrons abandoning their orders, tarnishing Jegede Jollof’s reputation and hindering potential growth.
Solution
In response to this challenge, Jegede Jollof turned to Vanus AI, an advanced GenAI application reliant on the AWS Cloud Computing Platform. Leveraging a sophisticated architecture that integrates various AWS services such as Amazon EKS, Amazon S3, Amazon DocumentDB, and Amazon Bedrock, Vanus AI provided a robust solution. The architecture comprises four main components: the main application, LLM, vector database, and document database. Built on Amazon EKS, the main application manages user and billing processes while delivering AI-driven functionalities. Amazon EKS ensures a highly available, secure, and scalable Kubernetes cluster, allowing Jegede Jollof to adjust computing resources according to demand. Amazon DocumentDB stores user data efficiently, benefiting from its seamless compatibility with MongoDB. Additionally, the connection to Amazon Bedrock Claude large model significantly reduces the cost of using extensive models up to almost 70%, enhancing Vanus AI’s capabilities while optimizing expenses.
Services Used
Vanus AI’s integration with Jegede Jollof’s operations relies on multiple AWS services. Amazon EKS provides the foundation for the main application, ensuring scalability and security. Amazon S3 is utilized for data storage, while Amazon DocumentDB serves as the primary database solution, facilitating seamless data management. The connection to Amazon Bedrock Claude large model enhances Vanus AI’s capabilities at a reduced cost, contributing to efficient operations and service delivery.
Outcomes
Before embracing Vanus AI and introducing their trusty assistant, Robin, Jegede Jollof faced a significant challenge. On average, out of every 50 customers who reached out to them online, they could, at best, cater to only 25, particularly during the bustling lunch hours when office workers sought to grab a quick meal. However, since Robin’s integration, they’ve seen a notable shift. They can now serve up to 45 customers, with the remaining 5 opting not to order, typically due to either item unavailability or personal circumstances. This change has sparked an all-encompassing boost in their revenue. Customers, in particular, have praised the service speed and have become regular customers thanks to this enhanced efficiency. What’s even more noteworthy is the increase in corporate clientele who now rely on Jegede Jollof for timely lunch deliveries, appreciating the reliability they provide. The introduction of Vanus AI has significantly enhanced productivity within their culinary team. With Robin efficiently managing online orders, all team members can focus on what they do best – crafting delectable dishes. This has eliminated the need for them to expand their workforce solely to manage online order processing.
