Availity increases productivity and accelerates code development with Amazon Q

Availity faced significant challenges that were affecting its operational efficiency. The primary issues stemmed from a lack of timely and efficient access to the large amount of information scattered across systems, including code and documentation. Availity teams struggled to find and access relevant information, significantly slowing down processes —from basic access to enterprise knowledge, to software development and data analysis.

Availity relies on enterprise knowledge accumulated over time on multiple data repositories, but this knowledge wasn’t easily accessible. As a result, Availity’s staff spent too much time finding and retrieving information to produce insights or to drive efficient code reviews. This inefficiency hindered teams and customers from obtaining information they needed, and affected internal operations, such as software development.

Initially, Availity tried to address these challenges by aggressively increasing staffing. However, this approach led to additional complications, including increased management needs and manual work, without enhancing operational efficiency. The company selected Amazon Q as the generative AI solution to improve information retrieval for analysis and insights, and to automate repetitive work.

Availity turned to AWS to address its operational challenges, given the generative AI capabilities of Amazon Q services, and the company's satisfaction with AWS’ security, privacy, and reliability. Availity worked with the AWS Professional Services team to help the company adopt Amazon Q Business, Amazon Q Developer, and Amazon Q in QuickSight. This lineup of services offered conversational AI assistance for solutions in areas Availity wanted to improve, such as data analysis, software development, and release management.

Availity started with targeted use cases that were visible, relatable, and impactful. Following the deployment of a general purpose chatbot for employee benefits and policy inquiries, the company moved to more complex applications with Amazon Q Business and Amazon Q Developer.

First, Availity created a team-wide Q&A conversational assistant with Amazon Q Business to make its release-management process more efficient. Then, the company integrated Amazon Q Developer to accelerate tasks across the software development lifecycle, boost code quality, and maintain high security standards. Amazon Q in QuickSight was added to the mix to deliver generative business intelligence capabilities to all users, providing the ability to generate insights from large enterprise data sources with natural language. The company also accelerated and improved a report known as Availity’s digital newspaper using Amazon Q in QuickSight to include explanations of key findings along with relevant visuals. This report serves as a single destination where employees can regularly access updated metrics and key business indicators, helping them stay informed about the company’s current business state.

In only six months, Availity implemented three Amazon Q services that dramatically improved access to its vast amounts of enterprise knowledge, data, and code. This allowed Availity teams to focus more on strategic projects and critical thinking, and less on searching for information and insights across teams and knowledge bases.

Availity cut their data research time in half, delivering insights twice as fast with Amazon Q Business conversational AI assistants that participate in team conversations and workflows. Amazon Q Business also revolutionized the release-management process by automatically retrieving and analyzing committed changes from source control. Availity’s development team uses Amazon Q Business to get quick, targeted information from a 100-pages document to generate insights, such as summaries of major changes or lists of affected customers. Review meetings are now quick and focused, dropping from 2 hours to 30 minutes —a 75 percent time savings. The solution also enhanced the team’s code analysis by showing changes clearly and in detail.

Using Amazon Q Developer, Availity’s development teams improved code, formatting, and complex problem-solving. Today, Availity’s developers focus on creative and problem-solving work while Amazon Q Developer supports coding activities that result in 33 percent of Availity’s total code-base. Availity also improved collaboration and ideation, helping developers reach solutions in minutes instead of days. For example, Availity’s development team quickly resolved a critical performance issue during a major system migration by interacting with Amazon Q Developer. The migration was successful and the interactions with Amazon Q Developer saved the team multiple days of work.

Availity leveraged Amazon Q in QuickSight to accelerate insights and decision-making with generative AI. Users can now explore Availity’s two trillion-row dataset in seconds using natural language, dramatically improving productivity by reducing reliance on data analysts. These AI-driven insights help optimize Availity's healthcare network, benefiting doctors, insurers, and patients. Additionally, Availity uses data stories, a capability of Amazon Q in QuickSight, to quickly create compelling visual publications that explain key business factors, establishing a common understanding of the company’s business data across the organization.

With the help of AWS, Availity uses Amazon Q services to automate knowledge-based tasks, enhance information retrieval, and augment its development teams’ capabilities. The AI-enhanced work environment means that Availity’s teams can focus on solving problems and innovating faster to deliver a better customer experience. Privat said, “It has saved us hours and a lot of stress. Combining AWS generative AI tools with the critical thinking of our engineers created a powerful platform for problem solving and finding fast and effective solutions.”