3 Ways Gen AI and AWS can Enhance Your Business

Gen AI and Your Business

Improving business operations with Generative AI on AWS provides companies with powerful tools to streamline workflows, automate complex tasks, and enhance decision-making processes. AWS offers a suite of advanced AI services, such as Amazon Bedrock, which enables businesses to develop custom AI models tailored to their specific needs. These models can analyze vast amounts of data, automate content creation, and optimize resource allocation, leading to more efficient operations. AWS’s robust and scalable infrastructure can quickly implement and scale AI solutions, ultimately driving productivity and innovation across the organization.

As an advanced AWS partner, we bring unparalleled expertise to architect, deploy, and optimize cloud solutions tailored to your unique needs. 

Improving the Customer Experience

The idea is to engage customers through multiple channels with seamless access to virtual agents across different collaboration tools and channels. Customers want easier access to answers and the option to complete certain transactions independently. Gen AI opens the door to implementing conversational voice and text-based chatbots. These interactions, in turn, can provide key data on customer interactions and insight into rising trends.

Professional Golfer’s Association Official App

The PGA needed a solution to improve the fan experience. Golf fans wanted leaderboards with real-time information, faster tournament updates, access to player profiles, and a more intuitive application.

In response, PGA partnered with the AWS Generative AI Innovation Center to build a new application prototype using Amazon Bedrock. The virtual assistant Amazon Bedrock manages uses methods such as retrieval-augmented generation (RAG), prompt engineering, vector data stores, and AWS’ top-of-the-line security environments. The newly implemented virtual assistant could compile player profiles and evaluate game performance. Better yet, its services could further extend to content producers, broadcasters, and average fans.

Increasing Employee Productivity

Companies are constantly searching for ways to increase their employees’ productivity. Generative AI can be trained using a company’s employee data, saving time and improving accuracy. Keeping a model’s training in-house reduces operation costs and speeds deployment. 

REPAY’s Internal Employee Network

REPAY is an omnichannel payment technology company that provides convenient, frictionless, and secure solutions for modernizing consumer and business payment systems. The Gen AI solution they wanted would allow employees to analyze internal data faster. However, the concern was that it could divert critical staff and resources toward the endeavor, undermining other initiatives.

They used the built-in connections to a pre-built webpage to quickly integrate the existing chatbot their employees were already using into the Amazon Q implementation within two sprints. An Amazon Kendra retriever was implemented to search rapidly and index private data sources to provide information as quickly and accurately as possible. With how much information teams at REPAY must handle, employees can now sort information and complete tasks more quickly.

Increasing Employee Productivity

Generative AI still offers plenty of potential to improve business functions.  As previously mentioned, it can help streamline how employees work and what content is built for customers.  It can be further applied toward boosting operations across a business structure.  With how Generative AI plays into predictive measures and interpreting internal flaws, it will only serve more roles as companies search for means of making operations more cost-effective.

LexisNexis’ Legal & Professional Operational Refinement

Automating specific processes that are labor intensive and open to human error can help accomplish in days what would normally take weeks or months. LexisNexis Legal & Professional is a global legal firm with a presence in over 150 countries. Their job is to wade through thousands of legal documents to provide clients with the most appropriate information. Specifics do vary from case to case, but work typically requires context windows for processing documents and providing data privacy for their customers.

Amazon Bedrock provides the basis for LexisNexis to give customers public access to a repository of accurate and exclusive legal information that is capable of returning comprehensive responses with linked legal citations. This database gives their employees considerable breathing room and improves the rate at which they can work with other law firms and their clients.

Conclusion