AWS Bedrock for Automation and Performance Boost

Modern technologies have become deeply rooted in the daily operations of an organization. Today, it is essential to provide a unique and fulfilling experience in order to create a long-lasting and fruitful relationship with the client. And automation is viewed as the key to that relationship.

The Agiliway software development team was contacted to join the development process to track a service provider-client relationship after the parties agreed on collaboration terms. The system consists of product lifecycles where suppliers manage separately the necessary parts based on the collaboration type. The key goal is to simplify the collaboration process through integrated accounting systems, messengers, reporting feature options, etc.

One of the latest additions to the platform is an AI-driven engine, AWS Bedrock, that allows automation of a handful of data processing and analysis, report generation, email automation, and more. In this article, we will analyze our experience with AWS Bedrock and its advantages while implementing an AI-based engine into the client’s solution.

Key Project Tasks and Challenges

Analyzing a large scope of data may be a challenging task, but it is rather impossible to write analytics that can answer any question a company owner or manager may have. To improve the existing solutions, our engineers utilized AWS Bedrock as an AI engine to boost the system’s performance and allow users to receive prompt replies to any question regarding the data within the platform. The implementation of AWS Bedrock transformed the client’s solution and brought significant value to their business.

Data reporting process includes collecting and analyzing all our client’s customers’ data. By generating regular reports, such as weekly reports, business owners can track the dynamics of changes, assess the level of customer satisfaction, and identify those that require additional attention. Based on the data obtained, we can plan our work for the next week and develop and implement the necessary measures to improve service and meet customer needs.

Solutions

Among the suggested solutions, the Agiliway team implemented the following functionality to boost the platform’s performance and automation of internal processes:

• A product feedback mailing list allows to receive customers’ opinions on the products. The evaluation is based on a 10-point scale, where 0 means that the product does not meet the needs, and 10 means complete customer satisfaction. Then, the system automatically generates a survey that is sent to the comments section. With the help of AI, we later analyze these surveys to learn more about the customers’ preferences, and expectations as well as which services they use the most. Previously, the client’s team had to manually read each comment, make notes, and analyze the reasons for satisfaction or dissatisfaction.
• Analysis of customers’ preferences and needs allows account managers to receive detailed information about each client and helps them to better understand their needs and preferences. AWS Bedrock helps to examine average statistics to determine which aspects of a product or service customers are satisfied with. Since the company offers a variety of products (for example, Internet subscriptions for $50, $100, or $200), the system will help them understand which ones are the most popular and which ones are less. AI collects all the information and puts it into a convenient Excel spreadsheet, which simplifies further data analysis.
• Communication analysis allows you to view a list of customers with their metrics, use custom fields and metrics for any business. AWS Bedrock enables the system to generate data on location, sales time, and customer contacts, which makes it possible to further in-depth data analysis. The metrics of the last contact and interaction help to maintain engagement with customers, and the monitoring system allows us to track the team’s productivity and the history of communication with customers. This flexibility and information content makes the system a valuable tool for any business.
• Email automation allows customers to select groups of contacts and send them emails. This is a useful tool for informing customers about new features, functions, or tools. For example, when we release a new feature, we can collect feedback from a specific group of users. This feedback will help us understand whether customers are satisfied with the new feature, or whether it needs to be improved and invested in. Users can request a demo presentation of the new feature from a manager, receive training materials, or share their impressions.

AWS Bedrock proved to be one of the best tools so far for data analytics. Its quick response time to customer-related questions facilitates customers’ decision-making process, hence, helping them grow their business.

Since the implementation of the AI-driven engine, the process of receiving feedback from customers has been automated, therefore, it minimizes manual processing of each feedback: users can simply send a request to AI to see if the customer is satisfied with the product or not.

The latest data show that after AWS Bedrock was implemented, the number of customers increased by 20% which also proves that the popularity of AI and level of trust are constantly growing.

The project is ongoing, hence, many new upgrades and changes are expected to be further implemented.

Summary

Today AI has become one of the most discussed tech trends. With a vast number of AI-driven engines, choosing the one that may bring significant benefit to a business is essential. Before the adoption of AI into your project, a careful examination of business needs shall be carried out in order to understand what solution is the best pick option.

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