Inspiration
The inspiration behind NextGen Aid came from a simple but critical question: What if someone experiences a medical emergency but is unable to call for help? Every year, countless lives are at risk because emergency response is delayed. Elderly people living alone, accident victims, and critically ill patients may be unable to communicate effectively during emergencies. At the same time, hospitals often receive prank or false emergency calls, making it difficult to prioritize genuine cases. We wanted to build an AI-powered solution that not only accelerates emergency response but also helps healthcare providers make informed decisions before dispatching resources.
What it does
NextGen Aid is an AI-powered emergency response solution that helps people receive medical assistance faster during critical situations.
When a user sends an emergency request through a phone call or text message, the AI agent analyzes the conversation, understands the user's intent, extracts important details such as the type of emergency and location, and converts the information into a structured JSON format.
The request is then orchestrated using UiPath Maestro, where a UiPath Coded Agent routes the emergency case to the appropriate hospital. A Human-in-the-Loop at the hospital reviews the request to verify whether it is genuine or fraudulent. If approved, the hospital initiates the ambulance dispatch process. If the request is determined to be fake or invalid, it is rejected and logged.
By combining Generative AI, intelligent automation, and human oversight, NextGen Aid reduces response times, minimizes false emergency requests, and enables healthcare providers to deliver timely medical assistance when every second counts.
How we built it
NextGen Aid is an intelligent emergency response system powered by Groq and UiPath Agentic Automation.
The workflow begins when a user sends an emergency request through a phone call or text message. An AI agent analyzes the conversation, extracts key details such as the type of emergency and location, and converts the information into a structured JSON format using Groq's high-speed LLM.
The request is then orchestrated by UiPath Maestro, which coordinates the end-to-end emergency workflow. A UiPath Coded Agent executes the business logic and routes the emergency request to the appropriate hospital. A Human-in-the-Loop validates whether the request is genuine before approving ambulance dispatch. If the request is identified as fake or invalid, it is rejected and logged for future analysis.
This combination of AI reasoning, intelligent orchestration, and human oversight creates a faster, smarter, and more reliable emergency response process.
Challenges we ran into
One of the biggest challenges was balancing speed with reliability. Emergency situations require immediate action, but hospitals also need confidence that requests are genuine before allocating valuable medical resources.
We also focused on:
Designing an AI workflow capable of understanding natural language from calls and messages. Converting unstructured conversations into structured data for downstream processing. Integrating AI decision-making with UiPath Maestro orchestration and coded agents. Incorporating Human-in-the-Loop approval to ensure responsible and trustworthy automation.
Accomplishments that we're proud of
Built an end-to-end AI-powered emergency response solution that transforms emergency calls or messages into actionable workflows in real time. Integrated Generative AI with Agentic Automation by combining Groq, UiPath Maestro, UiPath Coded Agent, and UiPath Studio Web into a seamless solution. Implemented Human-in-the-Loop validation, ensuring that hospitals can verify emergency requests before dispatching critical resources. Reduced manual intervention by automatically extracting emergency details, converting them into structured JSON, and orchestrating the response process. Designed a scalable architecture that can be extended to hospitals, emergency services, elderly care facilities, smart cities, and public safety organizations. Improved emergency response efficiency by enabling faster decision-making while helping reduce false or prank emergency requests. Demonstrated the real-world potential of Agentic AI, showing how AI can collaborate with humans to solve life-critical challenges rather than simply automate repetitive tasks. Created a practical healthcare innovation that highlights how intelligent automation can improve patient outcomes and optimize emergency service operations.
What we learned
Building NextGen Aid reinforced several important lessons:
AI is most effective when combined with human decision-making for critical scenarios. Intelligent workflow orchestration can dramatically reduce emergency response times. Structured data (JSON) enables seamless communication between AI agents and healthcare systems. Human-in-the-Loop validation increases trust and reduces the risk of false emergency responses. Agentic AI has the potential to solve real-world healthcare challenges beyond traditional automation.
What's next for NextGen Aid
Adding Voice assistant and more condition for false case validation
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