Streamlining Processes: USDA
The Arizona State University Artificial Intelligence Cloud Innovation Center, powered by AWS, in collaboration with the California Polytechnic Cloud Innovation Center (DxHub) and the U.S. Department of Agriculture (USDA), developed two AI-powered proofs of concept (POCs) to address key challenges in public engagement and IT support. These initiatives aim to enhance regulatory comment analysis and improve IT self-help services, leveraging AI for efficiency, accuracy, and automation.
Problem
The USDA faces challenges in efficiently managing and analyzing public comments on regulatory proposals. With thousands of submissions on Regulations.gov, manually categorizing and summarizing these comments is time-consuming and labor-intensive. There is a need for an automated system to conduct topic modeling, sentiment analysis, and AI-generated content detection while ensuring accurate clustering and summarization of public feedback.
Additionally, USDA’s IT support system sought to develop an AI-driven chatbot to provide self-help guidance for Tier 1 IT issues, reducing human intervention and improving response efficiency. The current process heavily relies on IT personnel to intervene on requests, leading to delays in issue resolution and increased support costs. A chatbot solution can enhance user experience, resolve common issues faster, and optimize IT operations.
Student Spotlight
The AI CIC is powered by ASU Student Workers. The following students were assigned to this project to develop this open-source solution in partnership with the AWS and ASU mentor team.
Role: UI/UX Designer and Frontend Developer | Connect with Arpita on LinkedIn
Experience: At USDA, I led the frontend development for the Public Comment Analysis platform, starting with mockups and driving the entire implementation. I designed a simple, USDA-branded interface with a seamless document queuing and processing flow. My end-to-end prototype received high praise, setting the foundation for development. I then optimized the frontend data architecture, integrating APIs and WebSockets to handle long-running document analysis efficiently.
This project taught me the power of designing technology that not only addresses technical challenges but also contributes to a larger societal impact.
Role: UI/UX Designer | Connect with Shakthi on LinkedIn
Experience: As a part of the USDA project, I created the low-fidelity design, wireframe, and collected the digital assets. It was a great experience creating low-fidelity designs and being able to understand the requirements of the project which was developing a tool to analyze public comments from regulations.gov, focusing on topic modeling, sentiment analysis, and AI-generated content detection, and transforming it into a seamless user interface.
Role: Backend Developer | Connect with Priyam on LinkedIn
Experience: Working on the USDA project has been an incredible opportunity to build a solution that bridges the gap between public participation and government rulemaking. Our team developed a sophisticated system that leverages AWS services and machine learning to analyze public comments more efficiently. One of the most rewarding aspects was creating an architecture that processes comments at scale and also identifies key themes and sentiment patterns that might otherwise be missed in manual review. The technical challenges of integrating various AWS services - from Step Functions orchestrating our workflow to SageMaker handling our clustering analysis - pushed us to think creatively about system design. But what makes this project truly meaningful is knowing that it helps ensure every voice is heard in the regulatory process, helping the government to be more responsive to public input.
Approach
The ASU AI Cloud Innovation Center developed an AI-driven Public Comment Analysis Tool to streamline USDA’s review process. Using Amazon SageMaker with DBSCAN clustering, the system automatically groups comments, assigns sentiment scores, and generates recommended actions for each category.
This AI-powered tool reduces manual workload, enhances decision-making, and improves regulatory transparency.
Key features:
- Automated Topic Modeling – Categorizes comments for quick analysis.
- Sentiment Analysis – Assigns overall sentiment to comment groups.
- AI-Generated Recommendations – Suggests data-driven actions.
- AWS-Powered Backend – Step Functions, Lambda, Amazon SageMaker, Bedrock (Sonnet 3.5), and API Gateway for real-time insights.
- User-Friendly UI – Built with React and Material UI, deployed via AWS Amplify.
Industry Impact
This AI-driven initiative is set to revolutionize public engagement and IT support. The Public Comment Analysis Tool will minimize the manual workload involved in reviewing public feedback, enabling faster insights and more data-driven policymaking. Through automated sentiment analysis and issue identification, the USDA can efficiently handle large volumes of comments, pinpoint key recommendations, and improve transparency in regulatory decisions.
The IT Help Desk Chatbot will enhance IT support by providing instant solutions to common issues, cutting costs, and boosting user satisfaction. Automating ticket resolution will speed up issue handling, optimize resource allocation, and refine the knowledge base.
For government agencies and businesses, these AI-powered solutions create a scalable approach to data analysis and IT automation, improving efficiency, engagement, and decision-making.
“My team and I really enjoyed working with the Cloud Innovation Center. Their work has successfully positioned us to improve how we analyze public feedback. Their custom analysis tool gave us quick insights into stakeholder comments, helping us identify key themes and concerns that might have otherwise been missed in the volume of submissions. The solution they built saved countless hours of manual review. I’m particularly impressed with how they approached the project and what they were able to achieve in just a few weeks. The best part is that this code is open source, making it easier for other federal agencies to benefit as well. I highly recommend the CIC.”
Fredy Diaz, Deputy Chief Data Officer, USDA
Potential for Wider Application
Beyond the USDA, these AI-driven solutions can benefit various industries. Government regulatory agencies can use automated public comment analysis to accelerate policy decisions, while legal and compliance teams can categorize and analyze large-scale regulatory feedback. Corporate IT support can reduce workload with AI-powered self-service chatbots, and universities and research institutions can enhance public engagement and streamline feedback processing. By leveraging AI for automation and data-driven insights, these solutions improve efficiency, lower costs, and enhance both public and internal service experiences.
Supporting Artifacts
| GitHub | Click here |
Next Steps
The USDA will build out this prototype for its public comment analysis needs, continuing to make the code open source for other federal agencies and users of Regulations.Gov.
About the ASU CIC
The ASU Artificial Intelligence Cloud Innovation Center (AI CIC), powered by AWS is a no-cost design thinking and rapid prototyping shop dedicated to bridging the digital divide and driving innovation in the nonprofit, healthcare, education, and government sectors.
Our expert team harnesses Amazon’s pioneering approach to dive deep into high-priority pain points, meticulously define challenges, and craft strategic solutions. We collaborate with AWS solutions architects and talented student workers to develop tailored prototypes showcasing how advanced technology can tackle a wide range of operational and mission-related challenges.
Discover how we use technology to drive innovation. Visit our website at ASU AI CIC or contact us directly at ai-cic@amazon.com.