AiroThon 2025 - Agentic AI Hackathon

Theme of AI Day - Agentic AI

• Cash Pool Prize - 75000 INR
• Registration Fee - Free 
• Eligibility - Fresher, Experienced Professionals, Engineering Students
• Stages and Timelines - Total 3 stages- Pre-screening, Online submission and presentations, top 10 teams for offline battle.
• Roll out - 16th July 2025
• Submission - 21th July 2025
• Pre-screening and Q&A - 27th July 2025
• Online Presentation - 11th August 2025
• Offline/Final (Event) - 22nd August 2025

All that you need to know about AiROthon

Overview:

• Platform for professionals, developers, engineers, data scientists
• AiroThon to find creative, practical solutions using MS Platform to real-world problems in BFSI, Healthcare and Manufacturing domains. 
• Focus on innovation and performance
• Encourages participants to go beyond functionality and bring groundbreaking ideas to life
• Designed to spark innovation, attract fresh talent, and foster collaboration between technology and performance experts

Who Can Participate?

• Talented professionals, coders, developers, engineers, and students across the NCR

Why Participate?

• Innovation
• Collaboration
• Learning
• Recruiting
• Growth
• Opportunity for students to stimulate creativity, develop innovative projects, and address real-world challenges
• Encourages thought-provoking questions, broader perspectives, and career growth

Dates

• Start of Pre-screening Submission (Online): 16th July, 2025
• Last Date of Pre-screening PPT Submission: 21st July, 2025
• Pre-screening Result Announcement: 27th July, 2025
• Round 1 Hackathon (Online): 11th August, 2025
• Round 2 Offline: 22nd August, 2025

Code of Conduct / Registration Criteria / Guidelines

• Eligibility Criteria:
  • Only Engineering students and working professionals are eligible
  • Open to students from all branches and academic years
  • Teams must consist of 2 to 3 members, per team.
• Submission Requirements:
  • All teams must submit a PPT for pre-screening using the prescribed template
  • All Teams must submit a Prototype for Round 1.
  • Non-adherence to template or guidelines results in disqualification
  • Submissions must be made before the deadline; late entries not accepted
• Hackathon Format:
  • Three rounds
    • Pre-screening: Teams choose a problem statement from domains (BFSI, Healthcare, Manufacturing) and submit the idea.
    • Round 1 Online
    • Round 2 Offline
  • Top 3 winners selected regardless of domain, based on innovation and excellence

Judging & Evaluation:

• Pre-screening based on:
• Innovation
• Feasibility
• Impact
• Clarity of solution in PPT
• Round 1: Live presentations/demos evaluated by industry experts and academic mentors
• No plagiarism or reuse of past projects
• Full disclosure required for reused code or projects; non-disclosure leads to dismissal.
• Round 2: offline presentations/demos evaluated by industry experts and academic mentors
• Feasibility of the Solution
• Impact in Industry
• Maintainability and scalability of solution.

Problem Statements

FinBot Connect

Industry: BFSI

Problem: Customers frequently experience long wait times or difficulty in obtaining specific information through traditional banking support channels. Banks aim to provide 24/7 personalized support while simultaneously reducing operational costs.

Challenge: Design and implement an AI-powered conversational agent (chatbot/voice bot) that can efficiently handle common customer inquiries, offer personalized financial advice, and seamlessly escalate complex issues to human agents.

FraudGuard (Real-time Anomaly Detection)

Industry: BFSI

Problem: Financial institutions are increasingly targeted by sophisticated fraud attempts in digital transactions. Existing rule-based systems are often reactive, generate high false positives, and struggle to adapt to new fraud patterns, resulting in significant financial losses.

Challenge: Develop a real-time AI-powered solution that detects and flags suspicious transactions with high accuracy, minimizes false positives, and provides actionable insights to fraud analysts.

Insurance - Smart Claims Processing

Industry: BFSI

Problem: Manual Auto insurance claims processing is often slow, labor-intensive, prone to errors, and vulnerable to fraud. This leads to customer dissatisfaction, increased operational costs, and delayed settlements.

Challenge: Develop an AI-driven solution to automate and expedite various stages of the insurance claims lifecycle, from First Notice of Loss (FNOL) to settlement. The solution should include intelligent document processing, fraud detection, and automated routing/triage of claims.

Insurance - Customer Value Enhancement

Industry: BFSI

Problem: Understanding and maximizing customer lifetime value (CLV) is challenging for insurance companies due to fragmented data and a lack of predictive insights. This impacts targeted marketing, retention strategies, and profitability.

Challenge: Develop an AI solution to analyze diverse customer data (policy history, interactions, demographics, external data) to predict customer churn, identify high-value segments, and recommend personalized engagement strategies to enhance customer loyalty and maximize CLV.

Compliance & Document Intelligence

Industry: BFSI

Problem: Manual review of regulatory circulars (for example issued by RBI and others) is slow and error-prone

Challenge: Parsing native and scanned PDFs, extracting obligations, finding action items and impact areas relevant to the financial organization, ensuring compliance.

GreenCraft

Industry: Manufacturing

Problem: Manufacturers are under increasing pressure to reduce their environmental footprint, optimize energy consumption, and minimize waste across their production processes, but identifying precise areas for improvement is complex.

Challenge: Develop an AI solution that monitors energy consumption, waste generation, and resource utilization in real-time within manufacturing processes, identifies inefficiencies, and recommends actionable strategies for reducing resource usage and carbon emissions.

Worker Safety & Efficiency

Industry: Manufacturing

Problem: Ensuring worker safety on the factory floor is a constant challenge, especially in hazardous environments. Additionally, optimizing human-machine collaboration can significantly improve operational efficiency.

Challenge: Build an AI-powered system to enhance worker safety by detecting hazardous situations (e.g., un-worn PPE, unauthorized zone entry, fatigue) using computer vision and IoT sensors. Simultaneously, optimize human-robot/machine collaboration for improved efficiency using real-time data analytics.

AI HR Buddy

Industry: HR

Problem: Employees feel disconnected in remote setups.

Challenge: Create an agent that tracks employee sentiment via conversations/emails (privately), nudges for wellness breaks, suggests policy clarifications, and books leave—autonomously.

9. API Governance & Modernization

Industry: Technology / Enterprise IT

Problem: Manual API discovery, documentation, and scoring is inefficient

Challenge: Extracting APIs across systems, ensuring accuracy, scalability, and adaptive learning.

Important date and Deadlines -

Registration deadline - 

21-July-2025, 12:00 AM