BugendaiTech is an AWS partner with a team of developers with expertise in using the AWS platform. The company real estate recommendation engine uses AI and ML to recommend properties based on image and feature selection. It can be quickly implemented without building and deploying a recommendation system. In addition, with AWS campaign analytics, businesses can get data insights to improve engagement and conversion.
Other AWS services used by BugendaiTech include EC2, S3, and RDS. The ultimate goal of the AWS recommendation engine is to create a real estate recommendation using AI in the AWS cloud environment.
95% reduction in time to gather worldwide daily football match information.
100% errors eliminated by automation in the figures and information digested.
Amazons cloud computing platform, AWS (Amazon Web Services), is extensive and constantly expanding. It combines infrastructure as a service (IaaS), platform as a service (PaaS), and packaged software as a service (SaaS) products. Amazon Web services are tools that allow businesses to store and process data, run applications, and manage their network.
One of the essential factors in reducing costs for a company is the ability to scale up or down based on demand. AWS offers that flexibility by allowing you to build and operate infrastructure.
We have aimed to solve problems using our expertise in favor of businesses. Our knowledge and skill have been established using various AWS cloud platform services and technologies, including Database storage, cloud machine learning, and content delivery services.
It could be the greatest nightmare for new business owners and startups to find themselves stuck with Too many moving parts and no idea where to begin; developer velocity is hampered by poorly architected infrastructure.
BugendaiTech Real Estate Recommendation Engine helps you choose your favorite property based on image and house feature selection within minutes; through its AI and ML-powered engines, you get the best-desired results for your dream property based on all your considerations. In addition, you can implement a customized personalization recommendation system powered by ML in just a few clicks without the burden of building, training, and deploying a do-it-yourself.
It is more than just recommending products that are right for you. It is about understanding your needs and preferences to tailor the recommendation to your situation. In addition, we can learn about customers through our usage data and predict what products would be beneficial. This helps boost engagement and conversion.
In the past 4 years we have collaborated and provided consultation for 25 + projects wherein our team was able to reduce the cost of setting up in house infrastructure and managing resources by 50%.
Data migration is to streamline the procedure for businesses, cut down on the number of processes, and provide the best service possible. After data analysis and transformation, the objective is to migrate the data from the Salesforce cloud to an AWS cloud database which has been the biggest concern of many business owners. The Real-time data events are handled by streaming data pipelines and are transformed using various ETL applications.
Did you know, With the help of the potent tool known as campaign analytics, you can see the behavioural characteristics that make up campaign interactions and discover how they affect the consumer route to conversion? The performance, scale, and pricing of AWS analytics services are optimised to provide you with the best results for your needs. In addition, they are explicitly designed to assist you in swiftly extracting data insights using the best tool for the task.
While we recognized that many new businesses struggle to compete in the market due to this issue, we nevertheless intended to achieve our objectives and give the most significant outcomes to aid our customers long-term survival.
Amazon Ec2 is a virtual machine-based service for running applications in the cloud.AWS Cloud provides a reliable infrastructure on demand for all your computing platforms also, Ec2 comes off as a scalable and secure option to deploy your full-scale applications. Customers can also use their service to manage many virtual machines using AWS.
Amazon Ec3 is an object storage service that provides secure online data storage for any file type. As a result, customers can store files in the cloud without paying for expensive storage space on their premises. They can also use S3 to transfer files between locations more quickly than a conventional LAN connection would allow.
Amazon RDS is a relational database offered by Amazon that provides 8 different relation databases managed and hosted on AWS Cloud. In addition, customers can choose from several other pricing models depending on how many resources they need from each type of service offered by AWS.
With the Amazon recommendation engine, you can implement a customized personalization recommendation system powered by ML in just a few clicks without the burden of building, training, and deploying a do-it-yourself.
It is more than just recommending products that are right for you. It is about understanding your needs and preferences as an individual so that your recommendation is tailored to your unique situation. With this, we can learn about customers through our usage data and make intelligent predictions about what kind of products would be most beneficial. This helps us boost engagement and conversion.
The ultimate goal of Bugendaitech AWS recommendation Engine is to create a real estate recommendation using AI-based techniques in the AWS cloud environment. AWS environment is the cloud-managed infrastructure that empowers scalability and traffic load balancing.
The AWS recommendation process runs in the backend and in correspondence to frontend UI, which helps to provide an end-to-end system deployed on IOS, Android, etc., specially designed for retail state buyers and property agents.
The recommendation engine used an AI-powered machine, and AI houses similarities based on client-preferred images as input.
Daily automatic extraction of football websites that include details about all football matches occurring around the globe . We tend to collect these details through a web scraper like selenium and storing the data into an AWS database. Additionally our ETL pipeline was powered for scraping unstructured historical data of the last 15 years from the website as well as daily scraping of new data. The solution is fine tuned to be scalable and process 50 M + records in one go.
This approach resulted in reducing time taken to collect the information about daily football matches in the entire world by 95 % without any manual efforts . Also automation leaves no space for errors in the figures and information digested. Hence through a dynamic AWS data pipeline, we aim to build an AI-based algorithm to scrape and transform the entities of data on the website into the structured and relational format, storing and mapping it across various database tables.
The collection of procedures to transfer data from one or more sources into a database, such as a data warehouse, is an ETL(Extract Transform Load) pipeline. The three interdependent data integration processes, known as "extract, transform, and load," or ETL, are used to extract data from one database and transport it to another. Data can be loaded and then used for reporting, analysis, and the creation of helpful business insights.
An ETL pipelines goal is to prepare data for business intelligence and analytics. Therefore, it is necessary to transport, consolidate, and modify source data from many systems (CRMs, social media platforms, Web reporting, etc.) to match the characteristics and functions of the destination database in order to deliver insightful information.
The data transformation phase can be particularly resource-intensive in terms of I/O and CPU processing for large-scale, high-volume extractions. Teams of data engineers are frequently forced to choose more minor extractions due to this restriction. The data teams must also provide business rules in advance, which limits flexibility, increases maintenance costs, and sometimes complicates the process. In addition, the data is processed before it reaches its destination, preventing analysts from accessing the raw data, and the time to insight is relatively long.
Since our inception, we have provided our consumers with world-class results and services that help their reputable businesses have goodwill and strong roots. We expanded beyond our domestic markets and received an overwhelming response to stay motivated and work even more challenging. Our journey began with limited heads with imagination. Still, today we are rowing swiftly with a massive ship of excellent creativity and hard-working professionals that give us the potential to satiate the clients needs with the utmost professionalism, communication, and top-notch services.
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