Reducing Development Time by 30% Using Amazon Q with nnamu

nnamu is an AI startup that specializes in strategic reasoning for businesses, with a focus on supply chain and procurement negotiations. The startup previously powered these capabilities with a legacy monolithic application, which was challenging to scale and maintain. nnamu wanted to rebuild the application on AWS, but its legacy system posed a number of challenges.

The startup’s existing code base was developed by an external vendor and lacked documentation. As a result, it was difficult for new members of its in-house development team to understand the system’s architecture and functionality. nnamu needed not only to improve the quality of its code but also to get developers up to speed. The startup also wanted to facilitate better collaboration across teams and make it simpler to retrieve enterprise information.

After consulting with the AWS team, nnamu began to evaluate Amazon Q for the project. “We needed a cloud-based solution that every developer could use within their own integrated development environment,” says Rahul Gupta, senior engineer at nnamu. “Amazon Q fits our use case, providing a private offering that we can integrate securely into our code base.”

To streamline the modernization project, nnamu implemented Amazon Q into every stage of the development lifecycle. The startup provided each team member with a subscription to Amazon Q Developer, a generative AI–powered assistant for software development that generates code suggestions in near real time. Using this tool, developers can quickly identify areas to optimize code, improving quality and consistency.

Product owners create detailed prompts describing the requirements and functionalities of new features, systems, or products. Developers then use Amazon Q Developer to generate code snippets based on the provided prompts and architectural requirements. During development and implementation, they integrate Amazon Q Developer into their workflows, receiving near real-time code suggestions and completions.

The acceptance rate of code generated by Amazon Q Developer is 33 percent, and the tool writes 46 percent of nnamu’s code. “We see the impact of Amazon Q Developer on our code quality every single day in our development work,” says Tolu Gbakinro, lead engineer at nnamu. “Our code quality has vastly improved because Amazon Q tells us exactly how we can improve.”

Amazon Q generates test cases and scripts based on the application’s requirements and functionality, helping developers validate a solution’s performance. Developers also use Amazon Q to create deployment scripts, configuration files, and documentation, making it simpler to update and improve the application over time.

In addition to Amazon Q Developer, nnamu uses Amazon Q Business, a generative AI assistant that empowers employees with enterprise knowledge and data. This tool integrates with nnamu’s project management software and ingests technical documentation, human resources policies, and project management spaces into a natural language chatbot. Employees can quickly find answers to questions such as “Why did we choose this architecture?” or “What is the policy for this specific area?” The chatbot provides a centralized source of knowledge on the startup’s processes and decisions. With these capabilities, nnamu has improved employee onboarding, facilitated collaboration between teams, and made it simpler for developers to retrieve information.

Using Amazon Q, nnamu has reduced development time by 30 percent, effectively accelerating the modernization project. The new serverless application is built using several AWS services, including AWS Lambda, a serverless, event-driven compute service, and Amazon DynamoDB, a NoSQL, fully managed database. These serverless capabilities, combined with Amazon Q, empower nnamu to continually scale its product, maintain high code quality, and rapidly deliver new features to its customers.

“The time saved isn’t just invested in the next feature, but also in our talent,” says Martin Walter, co-CEO and chief technology officer at nnamu. “We are growing rapidly and have hired many new people. Amazon Q helps us bring everyone up to speed because we prioritize learning and trying new things.”

With a modern foundation in place, nnamu will integrate Amazon Q and generative AI even further into its development process and products. The startup intends to use generative AI across the entire product lifecycle, from creating rapid prototypes for user testing to maintaining and enhancing existing code bases.

“Using Amazon Q has empowered us to swiftly generate accurate documentation, efficiently troubleshoot errors, and foster an informed workforce,” says Walter. “Our work with the AWS team extends beyond product usage; it is a comprehensive engagement that drives innovation, furthers technological advancement, and sets a standard for future-oriented business operations.”