Inspiration

Institution-related complaints may be handled by different departments, making it difficult to identify connected cases and track their progress in one place. We were inspired to create a solution that helps officials improve complaint visibility, coordination, and accountability.

What it does

Case Lens is an AI-assisted complaint monitoring platform designed to identify potentially related complaints across departments. It provides a unified, institution-wise dashboard to view complaint details, monitor case status, track deadlines, and review AI-generated suggestions.

How we built it

We propose a web-based platform with a dashboard for institution profiles, complaint tracking, and case-status monitoring. An AI component can analyze complaint text and relevant institution details to suggest potentially related cases. The platform can use a backend API and database to manage complaint records, while officials retain control over final decisions.

Challenges we ran into

A key challenge is identifying genuinely related complaints without incorrectly linking unrelated cases. Complaints may use different wording while describing the same issue. Another challenge is organizing information from different departments into a consistent format while maintaining appropriate data access and privacy.

Accomplishments that we're proud of

We developed the Case Lens concept around a practical institutional problem and designed a unified workflow for complaint monitoring. Our proposed approach combines AI-assisted case matching with institution-wise tracking, deadline visibility, and human review to support better-informed decisions.

What we learned

We learned that effective AI solutions require more than a model. Reliable data, careful matching, privacy protection, clear workflows, and human oversight are all important when applying AI to institutional complaint management.

What's next for Case Lens

Our next steps are to develop a working prototype, implement and evaluate complaint-similarity detection, create institution-wise dashboards, and introduce deadline alerts and case-history tracking. We also plan to evaluate incorrect matches and incorporate feedback from officials to improve the system.

Built With

ai
css3
html5
javascript
ml
modeltraining
natural-language-processing
python
vectorsearch

Submitted to

MineArena 1.0

Created by

I contributed to the CaseLens project by understanding the problem of scattered complaints and helping explain our AI-based solution. I also helped prepare the project presentation and explain its features, workflow, and benefits. Through this project, I learned how AI can help identify related complaints and improve coordination between departments.

Abhishek Krishna
Prem NM
Prajwal Malagi
Vivekananda swamy CM