Apply Now: MSME AI Grand Challenge (India)

Deadline: August 30, 2025

To proactively identifying potentially sick Micro, Small, and Medium Enterprises (MSMEs) using AI-powered predictive systems, Tamil Nadu Startup and Innovation Mission (TANSIM) branded as StartupTN, in collaboration with Tamil Nadu e-Governance Agency (TNeGA), invites startups and AI professionals to address a crucial concern.

Traditional risk assessment methods often fail to detect early signs of distress in MSMEs, resulting in delayed interventions and compounding financial instability.

Problem Statement

Develop an AI – driven early warning system that leverages proxy indicators such as electricity consumption and Udyam metadata to identify potentially sick MSMEs in Tamil Nadu and flag them for proactive support.

Technology Areas

Machine learning
Deep learning
Natural language processing Genetic algorithms.

Benefits

Collaboration with Government: Implementation opportunities with the MSME Department.
Networking Benefits: Talent exposure to key partners in the AI and governance sectors.

Eligibility Criteria

Startups
Professionals in AI, data science or related tech fields.

How can one participate?

Participants must submit registration details via the Open Innovation portal, including a pitch deck with concept note covering:
- Problem identification
- Proposed solution approach
- Team capabilities and track record

Procedure Post Submission

Hackathon:
- Day 1: Problem walkthrough sessions with mentors and the technical hackathon begin
- Day 2: Continued development, testing, mentoring, followed by a pitch to the Jury
- In a pitch, a short presentation deck should cover:
  - Architecture & Data pipeline
  - AI/ML model design (classification/regression/anomaly detection)
  - Tech stack and infrastructure
  - UI/UX and deployment methodology
  - Business model (if applicable)
Mentoring and access to Proxy Datasets:
- Top 10 teams from Hackathon will receive mentoring by domain experts
- Access to Proxy datasets resembling electricity consumption, metadata and others
Final Pitch for pilot with MSME Department:
- Evaluation is based on:
  - Model architecture, training logic, and hyperparameters.
  - Dataset structure used and preprocessing details.
  - Performance benchmarks and test case results.
  - Deployment feasibility.
Promising solutions will be eligible for a post-challenge contract for deployment