AI-Powered DMS Complaint Management System (Self-Initiated Learning Project – Prototype Stage)
Tools Used: Lovable AI, Relevance AI, Make.com
This self-driven project was built to explore AI-generated app development and understand how Dealer Management Systems (DMS) handle multi-role complaint workflows across customers, dealers, and admins. The system was created using Lovable (AI app builder) .
Key Features and Workflow:
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Role-Based Login System
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Complaint Lifecycle Management
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Dealer Assignment System
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Admin Dashboard
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Dealer Dashboard
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Customer Dashboard
Purpose & Outcome:
This project served as a practical exploration into building intelligent complaint systems using AI and low-code tools. It helped develop skills in:
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AI prompting
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Role-based architecture
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Full-stack logic flow
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Integration of external services like Relevance AI and Make
Current Status:
The system is in prototype stage, with login, complaint submission, tracking, and partial dealer assignment working. Backend linking between users and roles is implemented, and automation pipelines are being explored.
Challenges Faced:
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Real-time data syncing between role dashboards
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Handling dynamic role routing within Lovable’s builder constraints
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Ensuring complaint-to-dealer linkage without breaking UI logic
Fig 1.1 - Home page
Fig 1.2 - Complaint submission form
Fig 1.3 - Complaint tracking page
Fig 1.4 - Admin dashboard
Fig 1.5 - Report and analysis page
Results
- Prototype demonstrates a complete complaint journey - submission, tracking, dealer assignment and admin oversight - in one place.
- Replaces scattered phone and email complaint handling with a single, role-aware system of record.
- Validated the architecture for AI-assisted routing and reporting before committing to a full production build.
